Abstract:

Systems and methods are described relating to detecting an indication of
at least one attribute of an individual; accepting sensor data about the
individual; and presenting a set of health care options at least
partially based on the detecting an indication of at least one attribute
of the individual and the accepting sensor data about the individual.

Claims:

1. A system comprising:means for detecting an indication of at least one
attribute of an individual;means for accepting sensor data about the
individual; andmeans for presenting a set of health care options at least
partially based on the detecting an indication of at least one attribute
of the individual and the accepting sensor data about the individual.

2. The system of claim 1, wherein the means for detecting an indication of
at least one attribute of an individual comprises:means for detecting at
least one physical attribute associated with the at least one individual.

3-4. (canceled)

5. The system of claim 2, wherein the means for detecting at least one
physical attribute associated with the at least one individual
comprises:means for detecting at least one physical impairment associated
with the at least one individual.

6-7. (canceled)

8. The system of claim 2, wherein the means for detecting at least one
physical attribute associated with the at least one individual
comprises:means for detecting at least one physical diagnosis associated
with the at least one individual.

9. (canceled)

10. The system of claim 1, wherein the means for detecting an indication
of at least one attribute of an individual comprises:means for detecting
at least one of a current treatment or a proposed treatment associated
with the at least one individual.

11. The system of claim 1, wherein the means for detecting an indication
of at least one attribute of an individual comprises:means for detecting
the at least one attribute from a medical history associated with the at
least one individual.

12. The system of claim 1, wherein the means for detecting an indication
of at least one attribute of an individual comprises:means for detecting
the at least one attribute from a personal medical history associated
with at least one individual.

13. The system of claim 1, wherein the means for detecting an indication
of at least one attribute of an individual comprises:means for detecting
the at least one attribute from a family medical history associated with
the at least one individual.

14. The system of claim 1, wherein the means for detecting an indication
of at least one attribute of an individual comprises:means for detecting
at least one mental attribute associated with the at least one
individual.

15-17. (canceled)

18. The system of claim 14, wherein the means for detecting at least one
mental attribute associated with the at least one individual
comprises:means for detecting at least one mental impairment associated
with at least one individual.

19. (canceled)

20. The system of claim 14, wherein the means for detecting at least one
mental attribute associated with the at least one individual
comprises:means for detecting at least one mental diagnosis associated
with at least one individual.

21-22. (canceled)

23. The system of claim 1, wherein the detecting an indication of at least
one attribute of an individual comprises:means for detecting the at least
one attribute associated with the at least one individual from a health
care provider.

24-25. (canceled)

26. The system of claim 1 wherein the means for accepting sensor data
about the individual comprises:means for accepting sensor data from a
remote location.

27. The system of claim 1 wherein the means for accepting sensor data
about the individual comprises:means for accepting brain sensor data.

28. The system of claim 27 wherein the means for accepting brain sensor
data comprises:means for accepting data from at least one
neuroprosthetic.

29. The system of claim 27 wherein the accepting brain sensor data
comprises:means for accepting data from at least one brain-computer
interface.

30. The system of claim 29 wherein the means for accepting data from at
least one brain-computer interface comprises:means for accepting data
from at least one invasive brain-computer interface.

31. The system of claim 29 wherein the means for accepting data from at
least one brain-computer interface comprises:means for accepting data
from at least one partially invasive brain-computer interface.

32. The system of claim 31 wherein the means for accepting data from at
least one partially invasive brain-computer interface comprises:means for
accepting data from at least one electrocorticography electrode.

33. The system of claim 29 wherein the means for accepting data from at
least one brain-computer interface comprises:means for accepting data
from at least one non-invasive brain-computer interface.

34. The system of claim 33 wherein the means for accepting data from at
least one non-invasive brain-computer interface comprises:means for
accepting data from at least one wireless brain sensor.

35-37. (canceled)

38. The system of claim 1 wherein the means for accepting sensor data
about the individual comprises:means for accepting at least one of oxygen
sensor data, electricity sensor data, chemical sensor data, or
temperature sensor data.

39-53. (canceled)

54. The system of claim 1 wherein the means for presenting a set of health
care options at least partially based on the detecting an indication of
at least one attribute of the individual and the accepting sensor data
about the individual comprises:means for presenting at least one of
surgery, prescription drug therapy, over-the-counter drug therapy,
chemotherapy, radiation treatment, ultrasound treatment, laser treatment,
a minimally invasive procedure, antibody therapy, cryotherapy, hormonal
therapy, or gene therapy.

55. (canceled)

56. The system of claim 1 wherein the means for presenting a set of health
care options at least partially based on the detecting an indication of
at least one attribute of the individual and the accepting sensor data
about the individual comprises:means for presenting at least one of a
diagnosis option set or a treatment option set.

57. The system of claim 1 wherein the means for presenting a set of health
care options at least partially based on the detecting an indication of
at least one attribute of the individual and the accepting sensor data
about the individual comprises:means for presenting the set of health
care options at least partly based on at least one of a standard of care,
an expert opinion, an insurance company evaluation, or research data.

58. The system of claim 1 wherein the means for presenting a set of health
care options at least partially based on the detecting an indication of
at least one attribute of the individual and the accepting sensor data
about the individual comprises:means for presenting at least one of a
list of diagnosticians, a list of clinicians, a list of therapists, a
list of dentists, a list of optometrists, a list of pharmacists, a list
of nurses, a list of chiropractors, or a list of alternative medicine
practitioners.

59. The system of claim 1 wherein the means for presenting a set of health
care options at least partially based on the detecting an indication of
at least one attribute of the individual and the accepting sensor data
about the individual comprises:means for presenting at least one list of
treatment centers.

60. (canceled)

61. The system of claim 1 wherein the means for presenting a set of health
care options at least partially based on the detecting an indication of
at least one attribute of the individual and the accepting sensor data
about the individual comprises:means for using at least one third party
reference to present the set of health care options.

62. (canceled)

63. The system of claim 1 wherein the means for presenting a set of health
care options at least partially based on the detecting an indication of
at least one attribute of the individual and the accepting sensor data
about the individual comprises:means for detecting an individual's input
regarding a series of epileptic seizures, accepting data from an array of
brain sensor electrodes, and presenting a set of epilepsy medications and
a set of physicians that specialize in treating epilepsy based on
accepting the individual's input regarding a series of epileptic seizures
and based on accepting the data from the array of brain sensor
electrodes.

64. A computer-implemented method comprising:detecting an indication of at
least one attribute of an individual;accepting sensor data about the
individual; andpresenting a set of health care options at least partially
based on the detecting an indication of at least one attribute of the
individual and the accepting sensor data about the individual.

65-126. (canceled)

127. A system, comprising:circuitry for detecting an indication of at
least one attribute of an individual;circuitry for accepting sensor data
about the individual; andcircuitry for presenting a set of health care
options at least partially based on the detecting an indication of at
least one attribute of the individual and the accepting sensor data about
the individual.

128. A computer program product comprising:a signal-bearing medium
bearingone or more instructions for detecting an indication of at least
one attribute of an individual;one or more instructions for accepting
sensor data about the individual; andone or more instructions for
presenting a set of health care options at least partially based on the
detecting an indication of at least one attribute of the individual and
the accepting sensor data about the individual.

129. The computer program product of claim 128, wherein the signal-bearing
medium includes a computer-readable medium.

130. The computer program product of claim 128, wherein the signal-bearing
medium includes a recordable medium.

131. The computer program product of claim 128, wherein the signal-bearing
medium includes a communications medium.

132. A system comprising:a computing device; andinstructions that when
executed on the computing device cause the computing device todetect an
indication of at least one attribute of an individual;accept sensor data
about the individual; andpresent a set of health care options at least
partially based on the accepting an indication of at least one attribute
of the individual and the accepting sensor data about the individual.

133. The system of claim 132 wherein the computing device comprises:one or
more of a personal digital assistant (PDA), a personal entertainment
device, a mobile phone, a laptop computer, a tablet personal computer, a
networked computer, a computing system comprised of a cluster of
processors, a computing system comprised of a cluster of servers, a
workstation computer, and/or a desktop computer.

134. The system of claim 132 wherein the computing device is operable to
detect an indication of at least one attribute of an individual; accept
sensor data about the individual; and present a set of health care
options at least partially based on the accepting an indication of at
least one attribute of the individual and the accepting sensor data about
the individual.

Description:

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001]The present application is related to and claims the benefit of the
earliest available effective filing date(s) from the following listed
application(s) (the "Related Applications") (e.g., claims earliest
available priority dates for other than provisional patent applications
or claims benefits under 35 USC §119(e) for provisional patent
applications, for any and all parent, grandparent, great-grandparent,
etc. applications of the Related Application(s)).

[0022]The United States Patent Office (USPTO) has published a notice to
the effect that the USPTO's computer programs require that patent
applicants reference both a serial number and indicate whether an
application is a continuation or continuation-in-part. Stephen G. Kunin,
Benefit of Prior-Filed Application, USPTO Official Gazette Mar. 18, 2003,
available at
http://www.uspto.gov/web/offices/com/sol/og/2003/week11/patbene.htm. The
present Applicant Entity (hereinafter "Applicant") has provided above a
specific reference to the application(s) from which priority is being
claimed as recited by statute. Applicant understands that the statute is
unambiguous in its specific reference language and does not require
either a serial number or any characterization, such as "continuation" or
"continuation-in-part," for claiming priority to U.S. patent
applications. Notwithstanding the foregoing, Applicant understands that
the USPTO's computer programs have certain data entry requirements, and
hence Applicant is designating the present application as a
continuation-in-part of its parent applications as set forth above, but
expressly points out that such designations are not to be construed in
any way as any type of commentary and/or admission as to whether or not
the present application contains any new matter in addition to the matter
of its parent application(s).

[0023]All subject matter of the Related Applications and of any and all
parent, grandparent, great-grandparent, etc. applications of the Related
Applications is incorporated herein by reference to the extent such
subject matter is not inconsistent herewith.

[0025]In one aspect, a method includes but is not limited to detecting an
indication of at least one attribute of an individual, accepting sensor
data about the individual, and presenting a set of health care options at
least partially based on the detecting an indication of at least one
attribute of the individual and the accepting sensor data about the
individual. In addition to the foregoing, other apparatus aspects are
described in the claims, drawings, and text forming a part of the present
disclosure.

[0026]In one or more various aspects, related systems include but are not
limited to circuitry and/or programming for effecting the herein
referenced method aspects; the circuitry and/or programming can be
virtually any combination of hardware, software, and/or firmware
configured to effect the herein referenced method aspects depending upon
the design choices of the system designer.

[0027]In one aspect, a system includes but is not limited to means for
detecting an indication of at least one attribute of an individual, means
for accepting sensor data about the individual, and means for presenting
a set of health care options at least partially based on the detecting an
indication of at least one attribute of the individual and the accepting
sensor data about the individual. In addition to the foregoing, other
apparatus aspects are described in the claims, drawings, and text forming
a part of the present disclosure.

[0028]In one aspect, a system includes but is not limited to circuitry for
detecting an indication of at least one attribute of an individual,
circuitry for accepting sensor data about the individual, and circuitry
for presenting a set of health care options at least partially based on
the detecting an indication of at least one attribute of the individual
and the accepting sensor data about the individual. In addition to the
foregoing, other apparatus aspects are described in the claims, drawings,
and text forming a part of the present disclosure.

[0029]In one aspect, a computer program product includes but is not
limited to a signal-bearing medium bearing one or more instructions for
detecting an indication of at least one attribute of an individual, one
or more instructions for accepting sensor data about the individual, and
one or more instructions for presenting a set of health care options at
least partially based on the detecting an indication of at least one
attribute of the individual and the accepting sensor data about the
individual. In addition to the foregoing, other method aspects are
described in the claims, drawings, and text forming a part of the present
disclosure.

[0030]In one aspect, a system includes but is not limited to a computing
device and instructions that when executed on the computing device cause
the computing device to detect an indication of at least one attribute of
an individual, accept sensor data about the individual, and present a set
of health care options at least partially based on the accepting an
indication of at least one attribute of the individual and the accepting
sensor data about the individual. In addition to the foregoing, other
method aspects are described in the claims, drawings, and text forming a
part of the present disclosure.

[0031]The foregoing is a summary and thus may contain simplifications,
generalizations, inclusions, and/or omissions of detail; consequently,
those skilled in the art will appreciate that the summary is illustrative
only and is NOT intended to be in any way limiting. Other aspects,
features, and advantages of the devices and/or processes and/or other
subject matter described herein will become apparent in the teachings set
forth herein.

BRIEF DESCRIPTION OF THE FIGURES

[0032]FIG. 1 illustrates an example of a health services planning and
matching system in which embodiments may be implemented, perhaps in a
device and/or through a network, which may serve as a context for
introducing one or more processes and/or devices described herein.

[0034]FIG. 3 illustrates an example of an operational flow representing
example operations related to health services planning and matching,
which may serve as a context for introducing one or more processes and/or
devices described herein.

[0035]FIG. 4 illustrates an example of a health services planning and
matching system in which embodiments may be implemented, perhaps in a
device and/or through a network, which may serve as a context for
introducing one or more processes and/or devices described herein.

[0040]FIG. 9 illustrates an example of an operational flow representing
example operations related to health services planning and matching,
which may serve as a context for introducing one or more processes and/or
devices described herein.

[0041]FIG. 10 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0042]FIG. 11 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0043]FIG. 12 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0044]FIG. 13 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0045]FIG. 14 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0046]FIG. 15 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0047]FIG. 16 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0048]FIG. 17 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0049]FIG. 18 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0050]FIG. 19 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0051]FIG. 20 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0052]FIG. 21 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0053]FIG. 22 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0054]FIG. 23 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0055]FIG. 24 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0056]FIG. 25 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0057]FIG. 26 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0058]FIG. 27 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0059]FIG. 28 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0060]FIG. 29 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0061]FIG. 30 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0062]FIG. 31 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0063]FIG. 32 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0064]FIG. 33 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0065]FIG. 34 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0066]FIG. 35 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0067]FIG. 36 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0068]FIG. 37 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0069]FIG. 38 illustrates an alternative embodiment of the operational
flow of FIG. 9.

[0070]FIG. 39 illustrates a partial view of an example article of
manufacture including a computer program product that includes a computer
program for executing a computer process on a computing device related to
health services planning and matching, which may serve as a context for
introducing one or more processes and/or devices described herein.

[0071]FIG. 40 illustrates an example device in which embodiments may be
implemented related to health services planning and matching, which may
serve as a context for introducing one or more processes and/or devices
described herein.

DETAILED DESCRIPTION

[0072]In the following detailed description, reference is made to the
accompanying drawings, which form a part hereof. In the drawings, similar
symbols typically identify similar components, unless context dictates
otherwise. The illustrative embodiments described in the detailed
description, drawings, and claims are not meant to be limiting. Other
embodiments may be utilized, and other changes may be made, without
departing from the spirit or scope of the subject matter presented here.

[0073]FIG. 1 illustrates an example system 100 in which embodiments may be
implemented. The system 100 includes a device 102. The device 102 may
contain, for example, sensor 104, and treatment planning module 104. The
device 102 may communicate over a network or directly with remote
treatment planning module 150 and/or remote health care services matching
unit 152. User 140 may interact directly or through a user interface with
device 102. Device 102 may communicate with service provider 160, which
may include health care services provider 162 and/or payer 170. Device
102 may accept sensor data 154 from sensor 180 proximal to a user 140 or
from remote sensor 182 to provide a plurality of health services options,
for example via treatment planning module 104. Device 102 may match a
selected health service option with an appropriate service provider via,
for example health care services matching unit 120. Service provider 160
may include, for example, health care services provider 162 and/or payer
170.

[0074]In FIG. 1, health care services matching unit 120 may solicit a
health care services option from a service provider 160. Such a
solicitation may include an invitation to bid in an auction, a reverse
auction, or the like. Results of such a solicitation may include matching
a doctor capable of providing a chosen health care services option with
the user 140 in need of the chosen health care services option, perhaps
according to one or more preferences provided by the user 140. Health
care services matching unit 120 may otherwise find a service provider 160
through the use of a directory or other listing of health services
providers.

[0075]In FIG. 1, the device 102 is illustrated as possibly being included
within a system 100. Of course, virtually any kind of computing device
may be used to implement the special purpose sensor 180 and/or special
purpose sensor 182, special purpose treatment planning module 104 and/or
special purpose health care services matching unit 120, such as, for
example, a programmed workstation, a programmed desktop computer, a
programmed networked computer, a programmed server, a collection of
programmed servers and/or databases, a programmed virtual machine running
inside a computing device, a programmed mobile computing device, or a
programmed tablet PC.

[0077]Treatment planning module 104 and/or health care services matching
unit 120 may access data stored in virtually any type of memory that is
able to store and/or provide access to information in, for example, a
one-to-many, many-to-one, and/or many-to-many relationship. Such a memory
may include, for example, a relational database and/or an object-oriented
database, examples of which are provided in more detail herein.

[0079]Alternatively, remote sensor 282 may generate sensor data from
signals received from a distance. Examples of such remote sensing include
the use of signal processing algorithms for a wireless sensor that can
classify different types of motion and closely monitor a person's
breathing and/or heart rate. For example, this type of sensor is useful
in monitoring premature babies in a neonatal intensive care unit.
Premature infants have very sensitive and fragile skin, which can make it
difficult to directly attach sensors to them. A remote sensor can
wirelessly monitor an infant's movements, including breathing and heart
rate. Similarly, the sensor can be installed in a home for elder care or
other outpatient monitoring. See also U.S. Pat. No. 6,315,719; U.S. Pat.
No. 7,387,607; and U.S. Pat. No. 7,424,409; each of which is incorporated
herein by reference.

[0081]In this way, the user 140, who may be using a mobile device that is
connected through a network with the system 100 and/or device 102 (e.g.,
in an office, outdoors and/or in a public environment), may generate a
plurality of health service options as if the user 140 were interacting
locally with the device 102 and/or system 100.

[0082]As referenced herein, the treatment planning module 104 and/or
health care services matching unit 120 may be used to perform various
data querying and/or recall techniques with respect to sensor data 250
and/or a plurality of health service options, in order to obtain and/or
present a plurality of health service options. For example, where the
sensor data 250 is organized, keyed to, and/or otherwise accessible using
one or more reference health-related status indicators such as symptom,
disease, diagnosis, or the like, treatment planning module 104 and/or
health care services matching unit 120 may employ various Boolean,
statistical, and/or semi-boolean searching techniques to match sensor
data 250 with one or more indications of health status and/or one or more
relevant health-related services options. Similarly, for example, where
user preference data is organized, keyed to, and/or otherwise accessible
using one or more service provider 160 interest profiles, various
Boolean, statistical, and/or semi-boolean searching techniques may be
performed by health care services matching unit 120 to match a given
health-related services selection 244 with a service provider 160 to
present, for example, a matched health-related service 246.

[0083]Many examples of databases and database structures may be used in
connection with the treatment planning module 104 and/or health care
services matching unit 120. Such examples include hierarchical models (in
which data is organized in a tree and/or parent-child node structure),
network models (based on set theory, and in which multi-parent structures
per child node are supported), or object/relational models (combining the
relational model with the object-oriented model).

[0084]Still other examples include various types of eXtensible Mark-up
Language (XML) databases. For example, a database may be included that
holds data in some format other than XML, but that is associated with an
XML interface for accessing the database using XML. As another example, a
database may store XML data directly. Additionally, or alternatively,
virtually any semi-structured database may be used, so that context may
be provided to/associated with stored data elements (either encoded with
the data elements, or encoded externally to the data elements), so that
data storage and/or access may be facilitated.

[0085]Such databases, and/or other memory storage techniques, may be
written and/or implemented using various programming or coding languages.
For example, object-oriented database management systems may be written
in programming languages such as, for example, C++ or Java. Relational
and/or object/relational models may make use of database languages, such
as, for example, the structured query language (SQL), which may be used,
for example, for interactive queries for information and/or for gathering
and/or compiling data from the relational database(s).

[0086]For example, SQL or SQL-like operations over one or more reference
health attribute and/or reference service provider may be performed, or
Boolean operations using a reference health attribute and/or reference
service provider may be performed. For example, weighted Boolean
operations may be performed in which different weights or priorities are
assigned to one or more of the reference health-related status attributes
and/or reference service providers, including reference health conditions
and/or reference service providers associated with various reference
health-related status attributes, perhaps relative to one another. For
example, a number-weighted, exclusive-OR operation may be performed to
request specific weightings of desired (or undesired) health reference
data or service providers to be included or excluded. Reference
health-related status attributes may include normal physiological values
for such health-related things as pain, reaction time, body or eye
movement, memory, alertness, blood pressure, or the like. Such normal
physiological values may be "normal" relative to the user 140, to a
subpopulation to which the user 140 belongs, or to a general population.
Similarly, reference service providers may be associated with, for
example, the general medical community, a medical specialty, a local
geographical area or the like.

[0087]Following are a series of flowcharts depicting implementations. For
ease of understanding, the flowcharts are organized such that the initial
flowcharts present implementations via an example implementation and
thereafter the following flowcharts present alternate implementations
and/or expansions of the initial flowchart(s) as either sub-component
operations or additional component operations building on one or more
earlier-presented flowcharts. Those having skill in the art will
appreciate that the style of presentation used herein (e.g., beginning
with a presentation of a flowchart presenting an example implementation
and thereafter providing additions to and/or further details in
subsequent flowcharts) generally allows for a rapid and easy
understanding of the various process implementations. In addition, those
skilled in the art will further appreciate that the style of presentation
used herein also lends itself well to modular and/or object-oriented
program design paradigms.

[0088]FIG. 3 illustrates an operational flow 300 representing example
operations related to health services planning and matching. In FIG. 3
and in following figures that include various examples of operational
flows, discussion and explanation may be provided with respect to the
above-described system environments of FIGS. 1-2, and/or with respect to
other examples and contexts. However, it should be understood that the
operational flows may be executed in a number of other environments and
contexts including that of FIGS. 17 and 18, and/or in modified versions
of FIGS. 1-2. Also, although the various operational flows are presented
in the sequences illustrated, it should be understood that the various
operations may be performed in other orders than those which are
illustrated, or may be performed concurrently.

[0089]After a start operation, operation 310 depicts accepting sensor data
relating to at least one indication of health status. For example,
treatment planning module 104 and/or device 102 may accept sensor data
relating to at least one indication of health status. In one embodiment,
sensor 280 may transmit sensor data 250 to device 102 relating to a
symptom or disease. The user 140 may be a patient having a medical
condition, an individual experiencing one or more symptoms, an
asymptomatic individual, or the like. Sensor data relating to at least
one indication of health status may also include indications for cosmetic
enhancement, pregnancy, or improvement in athletic performance. In
another embodiment, treatment planning module 104 accepting blood
pressure sensor data indicating a sustained rise in blood pressure over
time may present a plurality of health service options based on the
indication of high blood pressure received from the blood pressure
sensor. The user 140 may then analyze the plurality of health service
options to determine whether or not to proceed in finding a health
service provider for the presented options for addressing the detected
high blood pressure. In one embodiment, user 140 may wish to find a
health service provider to address one of a plurality of presented health
service options. In this case, health care services matching unit 120 may
provide, for example, an auction system by which user 140 can procure the
desired health care service, for example, in a given geographic area at a
competitive price.

[0090]Operation 320 depicts presenting a plurality of health service
options at least partly based on the at least one indication of health
status. For example, treatment planning module 104 and/or device 102 may
present a plurality of health service options at least partly based on
the at least one indication of health status. In one embodiment,
treatment planning module 104 may, based on accepted sensor data, present
a set of health service options according to one or more diagnoses or
treatment paths corresponding to symptom(s) or conditions.

[0091]In one embodiment, a stochastic model can be built to describe an
image, for example a medical image. The stochastic model may then be used
to compare other images in the same way that it compares other data
sequences. Such a system is useful in automatic screening of medical
image data to identify features of interest. The system can be used to
compare images of the same patient taken at different times, for example
to monitor progress of a tumor, or it could be used to compare images
taken from various patients with a standard image.

[0092]D. Nikovski, "Constructing Bayesian Networks for Medical Diagnosis
from Incomplete and Partially Correct Statistics," IEEE Transactions on
Knowledge and Data Engineering, Vol. 12:4, pp. 509-516 (2000). The paper
discusses several knowledge engineering techniques for the construction
of Bayesian networks for medical diagnostics when the available numerical
probabilistic information is incomplete or partially correct. This
situation occurs often when epidemiological studies publish only indirect
statistics and when significant unmodeled conditional dependence exists
in the problem domain. While nothing can replace precise and complete
probabilistic information, still a useful diagnostic system can be built
with imperfect data by introducing domain-dependent constraints. We
propose a solution to the problem of determining the combined influences
of several diseases on a single test result from specificity and
sensitivity data for individual diseases. We also demonstrate two
techniques for dealing with unmodeled conditional dependencies in a
diagnostic network. These techniques are discussed in the context of an
effort to design a portable device for cardiac diagnosis and monitoring
from multimodal signals.

[0093]FIG. 4 illustrates an example system 400 in which embodiments may be
implemented. The system 400 includes a device 102. The device 102 may
contain, for example, detector module 602, accepter module 604, and/or
presenter module 606. The device 102 may communicate over a network or
directly with remote treatment planning module 150 and/or remote health
care services matching unit 152. User 140 may interact directly or
through a user interface with device 102. Device 102 may communicate with
service provider 160, which may include health care services provider 162
and/or payer 170. Device 102 may accept user input to provide one or more
health services options, for example via detector module 602 and/or
accepter module 604. Device 102 may accept a selected health service
option and match it with an appropriate service provider via, for example
health care services matching unit 120. Service provider 160 may include,
for example, health care services provider 162 and/or payer 170.

[0094]In FIG. 4, the device 102 is illustrated as possibly being included
within a system 400. Of course, virtually any kind of computing device
may be used to implement the special purpose health care services
matching unit 120, special purpose detector module 602, special purpose
accepter module 604, and/or special purpose presenter module 606, such
as, for example, a workstation, a desktop computer, a networked computer,
a server, a collection of servers and/or databases, a virtual machine
running inside a computing device, a mobile computing device, or a tablet
PC.

[0096]Health care services matching unit 120, detector module 602,
accepter module 604, and/or presenter module 606 may access data stored
in virtually any type of memory that is able to store and/or provide
access to information in, for example, a one-to-many, many-to-one, and/or
many-to-many relationship. Such a memory may include, for example, a
relational database and/or an object-oriented database, examples of which
are provided in more detail herein.

[0101]FIG. 9 illustrates an operational flow 900 representing example
operations related to detecting an indication of at least one attribute
of an individual, accepting sensor data about the individual, and
presenting a set of health care options at least partially based on the
detecting an indication of at least one attribute of the individual and
the accepting sensor data about the individual. In FIG. 9 and in
following figures that include various examples of operational flows,
discussion and explanation may be provided with respect to the
above-described examples of FIGS. 4 through 8, and/or with respect to
other examples and contexts. However, it should be understood that the
operational flows may be executed in a number of other environments and
contexts, and/or in modified versions of FIGS. 4 through 8. Also,
although the various operational flows are presented in the sequence(s)
illustrated, it should be understood that the various operations may be
performed in other orders than those which are illustrated, or may be
performed concurrently.

[0102]After a start operation, the operational flow 900 moves to operation
910. Operation 910 depicts detecting an indication of at least one
attribute of an individual. For example, as shown in FIGS. 4 through 8,
detector module 602 can detect at least one attribute of an individual.
In an embodiment, accepter module 602 may accept a personal medical
history, for example, that includes an individual's blood pressure
history. Accepting at least one attribute of an individual may serve to
better indicate an individual's medical status to a health care provider,
for example. Some other examples of an attribute of an individual may
include results from a patient interview, results from an individual's
input into, for example, a computer station, and/or a medical history. In
some instances, accepter module 602 may include a computer processor.

[0103]Then, operation 920 depicts accepting sensor data about the
individual. For example, as shown in FIGS. 4 through 8, accepter module
604 can accept sensor data about the individual. In an embodiment,
accepter module 604 may accept data from a blood pressure cuff while
measuring an individual's blood pressure. Accepting sensor data may serve
further validate or invalidate the accepted indication of an individual's
attribute. Some examples of a sensor may include a movement sensor, a
glucose sensor, an oxygen sensor, a chemical sensor, a thermometer, an
optical sensor, and/or a biochip. In some instances, accepter module 604
may include a computer processor.

[0104]Then, operation 930 depicts presenting a set of health care options
at least partially based on the detecting an indication of at least one
attribute of the individual and the accepting sensor data about the
individual. For example, as shown in FIGS. 4 through 8, presenter module
606 may present a set of health care options at least partially based on
the accepting an indication of at least one attribute of the individual
and the accepting sensor data about the individual. In one embodiment,
presenter module 606 may, based on at least one accepted attribute of an
individual and accepted sensor data, present a set of health care options
according to one or more diagnoses and/or treatment paths corresponding
to symptom(s) or conditions indicated by the accepted attribute(s) of an
individual and accepted sensor data. Some examples of presenting a
plurality of health service options may include presenting at least one
physician, medication, exercise, health care facility, and/or medical
procedure. In some instances, presenter module 606 may include a computer
processor.

[0106]Operation 1002 illustrates detecting at least one physical attribute
associated with the at least one individual. For example, as shown in
FIGS. 4 through 8, physical attribute detector module 608 may detect at
least one physical attribute associated with the at least one individual.
In one instance, physical attribute detector module 608 can detect a
physical attribute associated with an individual, for example a weight
history. A physical attribute may include an attribute that may be
described and/or detected using senses, that has substance and/or a
material existence, and/or that may be acted upon by physical force. Some
examples of a physical attribute may include a biochemical measurement
such as blood sugar level, an appearance, and/or a physiological
measurement such as blood pressure, and/or skin conductivity. In some
instances, physical attribute detector module 608 may include a computer
processor.

[0107]Further, operation 1004 illustrates detecting at least one physical
symptom associated with the at least one individual. For example, as
shown in FIGS. 4 through 8, symptom detector module 610 may detect at
least one physical symptom associated with the at least one individual.
In one example, symptom detector module 610 can detect from an individual
and/or user interface a physical symptom, for example an indication of
influenza (e.g., a fever). A physical symptom may include a
manifestation, sign, and/or an indication of the presence of a disease
and/or some other bodily disorder and/or abnormality. Some examples of a
physical symptom may include pain, swelling, fever, rash, and/or
discoloration. In some instances, symptom detector module 610 may include
a computer processor.

[0108]Further, operation 1006 illustrates detecting at least one of an
indication or a measurement of at least one of pain, hypertension,
sweating, dizziness, lightheadedness, abnormal respiration, headache,
fatigue, nausea, fever, abnormal heart rhythm, motor weakness, or
abnormal heart rate. For example, as shown in FIGS. 4 through 8, specific
symptom detector module 612 can detect at least one of an indication or a
measurement of at least one of pain, hypertension, sweating, dizziness,
lightheadedness, abnormal respiration, headache, fatigue, nausea, fever,
abnormal heart rhythm, motor weakness, or abnormal heart rate. In one
example, specific symptom detector module 612 can detect an indication of
an individual's pain and a measurement of high blood pressure from a
patient interview. Pain may include a sensation of somatic hurt or
disorder and may include acute pain and/or chronic pain. Hypertension may
include chronically elevated blood pressure and may be considered to be
present when a person's systolic blood pressure is consistently about 140
mm Hg or greater and/or their diastolic blood pressure is consistently
about 90 mm Hg or greater. Sweating may include the excessive production
and/or evaporation of fluid excreted by the sweat glands in the skin.
Dizziness may include vertigo, disequilibrium, pre-syncope, and/or other
balance disorders. Lightheadedness may include a sensation of dizziness
and/or fainting. Abnormal respiration may include atypical and/or
pathological breathing patterns. Headache may include pain in the head,
neck, and/or upper back and may be a symptom of tension, migraine,
dehydration, eye strain, sinus disorders, and/or low blood sugar. Fatigue
may include muscle weakness and/or lack of strength. Nausea may include
the sensation of unease and/or discomfort in the stomach, often with the
urge to vomit. Fever may include an increase in internal body temperature
to levels above normal. Abnormal heart rhythm may include inconsistent
and/or irregular rhythmic contractions in the heart such as sick sinus
syndrome, atrial fibrillation, and/or atrial flutter. Motor weakness may
include a lack of strength and/or function in the portion of the central
nervous system involved in movement. An abnormal heart rate may include
an irregular heart contraction frequency such as bradycardia, tachycardia
or the like. In some instances, specific symptom detector module 612 may
include a computer processor.

[0110]Further, operation 1102 illustrates detecting at least one physical
impairment associated with the at least one individual. For example, as
shown in FIGS. 4 through 8, impairment detector module 614 can detect at
least one physical impairment associated with the at least one
individual. In one instance, impairment detector module 614 detects a
physical impairment including a bodily impairment associated with an
individual from the individual via a user interface. A physical
impairment may include a condition or function judged to be significantly
impaired relative to the usual standard of an individual of their group
and may include physical impairment, sensory impairment, and/or disease.
In some instances, impairment detector module 614 may include a computer
processor.

[0111]Further, operation 1104 illustrates detecting at least one of a
disease, an illness, or a bodily impairment. For example, as shown in
FIGS. 4 through 8, bodily impairment detector module 616 can detect at
least one of a disease, an illness, or a bodily impairment. In one
example, bodily impairment detector module 616 may detect an indication
of a disease and a bodily impairment from a database entry. A disease may
include an abnormal condition of an organism that impairs bodily
functions associated with one or more specific symptoms and signs and may
include discomfort, distress, dysfunction, injury, a disorder, a
syndrome, infection, and/or other atypical variation associated with
structure and/or function of the body. An illness may include any state
of poor health. Some examples of an illness may include cancer, the
common cold, influenza, pneumonia, and/or high cholesterol. A bodily
impairment may include a diminished ability in body function and/or
structure. In some instances, bodily impairment detector module 616 may
include a computer processor.

[0112]Further, operation 1106 illustrates detecting an impairment
associated with at least one individual including at least one of a
potential medication reaction or a potential susceptibility to a side
effect. For example, as shown in FIGS. 4 through 8, specific impairment
detector module 618 can detect an impairment associated with at least one
individual including at least one of a potential medication reaction or a
potential susceptibility to a side effect. In one example, specific
impairment detector module 618 may detect from a network storage location
an impairment associated with an individual including a potential
medication reaction and a potential susceptibility to a side effect. A
potential medication reaction may include a possible response a person
may exhibit resulting from at least one drug and/or medication
administered to the person. A potential medication reaction may include
an allergy and/or a drug and/or medication interaction with a separate
drug and/or medication. A potential susceptibility to a side effect may
include the probability a certain person may be vulnerable to a side
effect coupled with a specific drug and/or medication. Accepting an
impairment may further assist in presenting an appropriate therapy for
the individual by, for example, not presenting a therapy that may invoke
and/or trigger an undesired side effect and/or reaction. In some
instances, specific impairment detector module 618 may include a computer
processor.

[0114]Further, operation 1202 illustrates detecting at least one physical
diagnosis associated with the at least one individual. For example, as
shown in FIGS. 4 through 8, diagnosis detector module 620 can detect at
least one physical diagnosis associated with the at least one individual.
In a specific example, diagnosis detector module 620 may detect from a
memory device a physical diagnosis of epilepsy associated with the
individual. A physical diagnosis may include identifying a disease and/or
condition by its outward signs and/or symptoms. Some other examples of a
physical diagnosis may include identifying influenza and/or identifying
Alzheimer's disease. In some instances, diagnosis detector module 620 may
include a computer processor.

[0115]Further, operation 1204 illustrates detecting at least one diagnosis
of at least one of a cardiovascular disorder, a digestive disorder, an
endocrine disorder, a hearing disorder, an immune disorder, an inner ear
disorder, an integumentary disorder, a lymphatic disorder, a muscular
disorder, a nervous system disorder, a reproductive disorder, a
respiratory disorder, a skeletal disorder, a visual disorder, or an
urinary disorder. For example, as shown in FIGS. 4 through 8, disorder
detector module 622 can detect at least one diagnosis of at least one of
a cardiovascular disorder, a digestive disorder, an endocrine disorder, a
hearing disorder, an immune disorder, an inner ear disorder, an
integumentary disorder, a lymphatic disorder, a muscular disorder, a
nervous system disorder, a reproductive disorder, a respiratory disorder,
a skeletal disorder, a visual disorder, or an urinary disorder. In a
specific instance, disorder detector module 622 can detect from a user
interface a diagnosis of a respiratory disorder. A cardiovascular
disorder may include a disorder associated with the circulatory system
including the pumping and channeling of blood to and from the body and
lungs with the heart, the blood, and the blood vessels. Examples of a
circulatory disorder include high blood pressure, coronary heart disease,
atherosclerosis, or the like. A digestive disorder may include a disorder
associated with the esophagus, the stomach, the liver, the gallbladder,
the pancreas, the intestines, the rectum, the anus, and/or the digestive
system including digestion and processing food with salivary glands.
Examples of a digestive disorder include GERD, Crohn's disease, IBS, or
the like. An endocrine disorder may include a disorder associated with
the endocrine system including the pancreas, the pituitary gland, the
pineal body and/or the pineal gland, the thyroid, the parathyroids, the
adrenal glands, and/or communication within the body using hormones made
by the endocrine glands, such as the hypothalamus. Examples of an
endocrine disorder include diabetes, acromegaly, or the like. A hearing
disorder may include a full or partial decrease in the ability to detect
or understand sounds. Some examples of a hearing disorder may include
otosclerosis, deafness, and/or unilateral hearing toss. An immune
disorder may include a dysfunction of the immune system. Examples of an
immune disorder may include an immunodeficiency, such as malfunctioning
lymphocytes; autoimmunity, such as Coeliac disease and/or autoimmune
hepatitis; and/or hypersensitivity, such as asthma. An inner ear disorder
may include a balance disorder, such as vertigo, disequilibrium, and/or
pre-syncope. An integumentary disorder may include a disorder associated
with the integumentary system including the skin, hair, and/or nails,
such as psoriasis, eczema, dermatitis, or the like. A lymphatic disorder
may include a disorder associated with the lymphatic system including
structures involved in the transfer of lymph between tissues and the
blood stream and/or the lymph and the nodes and vessels that transport
lymph including the immune system, including defending against
disease-causing agents with leukocytes, and/or including the tonsils, the
adenoids, the thymus, and/or the spleen. Examples of a lymphatic disorder
include lymphedema, lymphadenopathy, or the like. A muscle disorder may
include a disorder associated with the muscular system including the
structure and/or movement of muscles. Examples of a muscle disorder
include muscular dystrophy, myasthenia gravis, an injury, such as a
strain, or the like. A nervous system disorder may include a disorder
associated with the nervous system including collecting, transferring,
and/or processing information with the brain, the spinal cord, the
peripheral nerves, and/or the nerves. Examples of a nervous system
disorder include multiple sclerosis, fibromyalgia, carpal tunnel
syndrome, or the like. A reproductive disorder may include a disorder
associated with the reproductive system including the sex organs, such as
ovaries, fallopian tubes, the uterus, the vagina, mammary glands, testes,
the vas deferens, seminal vesicles, the prostate, and/or the penis.
Examples of a reproductive disorder include erectile dysfunction,
endometriosis, fibroids, or the like. A respiratory disorder may include
a disorder associated with the respiratory system including the organs
used for breathing, the pharynx, the larynx, the trachea, the bronchi,
the lungs, and/or the diaphragm. Examples of a respiratory disorder
include emphysema, asthma, or the like. A skeletal disorder may include a
disorder associated with the skeletal system including the structural
support and protection with bones, cartilage, ligaments, and/or tendons.
Examples of a skeletal disorder include osteoporosis, arthritis,
tendonitis, a skeletal injury, such as a bone fracture, or the like. A
visual disorder may include a disease, impairment, and/or lack of
function in the eye and/or in visual perception. Some examples of a
visual disorder may include amblyopia, macular degeneration, glaucoma,
and/or blindness. A urinary disorder may include a disorder associated
with the urinary system including the kidneys, the ureters, the bladder
and/or urethra involved in fluid balance, electrolyte balance and/or the
excretion of urine. Examples of a urinary disorder include bladder
dysfunction, kidney disease, bladder or urethra infection, or the like.
In some instances, disorder detector module 622 may include a computer
processor.

[0117]Operation 1302 illustrates detecting at least one of a current
treatment or a proposed treatment associated with the at least one
individual. For example, as shown in FIGS. 4 through 8, treatment
detector module 624 can detect at least one of a current treatment or a
proposed treatment associated with the at least one individual. In one
instance, treatment detector module 624 may detect a current treatment
regime associated with a certain individual. A current treatment may
include one or a series of treatments recommended, administered, and/or
prescribed for a certain individual. A proposed treatment may include one
or a series of treatments recommended, prescribed, and/or not currently
administered to a certain individual. In some instances, treatment
detector module 624 may include a computer processor.

[0118]Operation 1304 illustrates detecting the at least one attribute from
a medical history associated with the at least one individual. For
example, as shown in FIGS. 4 through 8, medical history detector module
626 can detect the at least one attribute from a medical history
associated with the at least one individual. In one example, medical
history detector module 626 may detect an attribute from a medical
history including a record of diabetes therapy associated with a specific
individual. A medical history may include a list of previous illnesses,
symptoms, medicines, treatments, health risk factors, operations, and/or
doctor visits for an individual and/or a relation of an individual. In
some instances, medical history detector module 626 may include a
computer processor.

[0119]Operation 1306 illustrates detecting the at least one attribute from
a personal medical history associated with at least one individual. For
example, as shown in FIGS. 4 through 8, personal history detector module
628 can detect the at least one attribute from a personal medical history
associated with at least one individual. In an embodiment, personal
history detector module 628 may detect an attribute including, for
example, a list of surgeries from a personal medical history associated
with a specific individual. A personal medical history may include a list
of previous illnesses, symptoms, medicines, treatments, health risk
factors, operations, and/or doctor visits associated with at least one
individual. A personal and/or a family medical history may include life
history and/or social history characteristics such as smoking, drinking,
drug use, sexual history, exercise history, eating history, nutraceutical
history, or the like. In some instances, personal history detector module
628 may include a computer processor.

[0120]Operation 1308 illustrates detecting the at least one attribute from
a family medical history associated with the at least one individual. For
example, as shown in FIGS. 4 through 8, family history detector module
630 can detect the at least one attribute from a family medical history
associated with the at least one individual. In an example, family
history detector module 630 may detect an attribute including a list of
family members that have had epilepsy from a family medical history
associated with a specific individual. A family medical history may
include a list of previous illnesses, symptoms, medicines, treatments,
health risk factors, operations, and/or doctor visits associated with
family members related to the at least one individual. In some instances,
family history detector module 630 may include a computer processor.

[0122]Operation 1402 illustrates detecting at least one mental attribute
associated with the at least one individual. For example, as shown in
FIGS. 4 through 8, mental attribute detector module 632 can detect at
least one mental attribute associated with the at least one individual.
In one example, mental attribute detector module 632 may detect a mental
attribute including, for example, an indication of a learning disability
associated with a specific individual. A mental attribute may include an
attribute that may be related to and/or associated with basic mental
function and/or high-level brain function. Some examples of a mental
attribute may include an indication of cognitive disability, measurements
of brain activity, for example using functional MRI or near infra-red
technology, and/or measurements of mental development. In some instances,
mental attribute detector module 632 may include a computer processor.

[0123]Further, operation 1404 illustrates detecting at least one mental
symptom associated with the at least one individual. For example, as
shown in FIGS. 4 through 8, mental symptom detector module 634 can detect
at least one mental symptom associated with the at least one individual.
In one example, mental symptom detector module 634 may detect a mental
symptom including a stress level measurement associated with a specific
individual. A mental symptom may include a manifestation, sign, and/or an
indication of the presence of a disease and/or some other mental disorder
and/or abnormality. Some examples of a mental symptom may include tack of
attention, indication of stress, hyperactivity, nervousness, and/or lack
of responsiveness. In some instances, mental symptom detector module 634
may include a computer processor.

[0124]Further, operation 1406 illustrates detecting at least one
indication of anxiety, an appearance, a behavior, depression, fear,
inattention, a mood disturbance, a phobia, or a psychological test
result. For example, as shown in FIGS. 4 through 8, mental indication
detector module 636 can detect at least one indication of anxiety, an
appearance, a behavior, depression, fear, inattention, a mood
disturbance, a phobia, or a psychological test result. In one example,
mental indication detector module 636 can detect from a user interface an
indication of anxiety and depression. Anxiety may include feelings of
fear, apprehension, and/or worry and may be accompanied by physical
sensations. An appearance may include an outward, audible, and/or visible
aspect of a person and/or thing associated with a person. A behavior may
include the manner in which a person and/or thing associated with a
person acts and/or reacts. Depression may include a mental state
characterized by pessimism, a sense of inadequacy, despondence, despair,
a low level of energy, and/or a lack of activity. Fear may be caused by
impending danger, perceived evil, and/or pain, whether real or imagined.
Inattention may include the failure of a person to focus attention. A
mood disturbance may include a change in emotional state. A phobia may
include an irrational, and/or persistent fear of certain situations,
objects, activities, and/or people. A psychological test result may
include a sample behavior for inferring a certain generalization about a
person. For example, a personality test result may indicate that person
has obsessive/compulsive characteristics. In some instances, mental
indication detector module 636 may include a computer processor.

[0126]Further, operation 1502 illustrates detecting at least one
measurement associated with at least one of brain activity, cardiac
activity, vascular activity, peripheral neural signals, hemodynamic
activity, or metabolic activity. For example, as shown in FIGS. 4 through
8, mental activity detector module 638 may detect at least one
measurement associated with at least one of brain activity, cardiac
activity, vascular activity, peripheral neural signals, hemodynamic
activity, or metabolic activity. In one instance, mental activity
detector module 638 can detect a measurement associated with brain
activity. Brain activity may include the electrical activity of the
brain, such as that measured by EEG, MEG, or the like. Other brain
activity measurements may include functional MRI imaging, near infra-red
imaging, PET scanning, or the like. Cardiac activity may include
electrical activity in the heart, such as that measured by EKG or visual
imaging. Vascular activity may include any activity and/or function of
the circulatory system. Peripheral neural signals may include neural
signals sent through the peripheral nervous system. Hemodynamic activity
may include any activity associated with the circulatory system.
Metabolic activity may include any activity associated with the
biochemical reactions occurring in a living organism. In some instances,
mental activity detector module 638 may include a computer processor.

[0128]Further, operation 1602 illustrates detecting at least one mental
impairment associated with at least one individual. For example, as shown
in FIGS. 4 through 8, mental impairment detector module 640 can detect at
least one mental impairment associated with at least one individual. In
one example, mental impairment detector module 640 can detect a mental
impairment associated with a specific individual. A mental impairment may
include a condition or function judged by a health care provider to be
significantly impaired relative to the usual standard of an individual of
their group, and may include mental impairment, sensory impairment,
and/or mental disease. In some instances, mental impairment detector
module 640 may include a computer processor.

[0129]Further, operation 1604 illustrates detecting at least one
indication of at least one of a mood disorder, an anxiety disorder, a
psychotic disorder, an eating disorder, a developmental disorder, a
phobia, a communication disorder, a social disorder, or a personality
disorder. For example, as shown in FIGS. 4 through 8, mental disorder
detector module 642 may detect at least one indication of at least one of
a mood disorder, an anxiety disorder, a psychotic disorder, an eating
disorder, a developmental disorder, a phobia, a communication disorder, a
social disorder, or a personality disorder. In one instance, mental
disorder detector module 642 can detect from a user interface an
indication of a mood disorder in a specific individual. A mood disorder
may include a condition whereby the prevailing emotional mood is
distorted or inappropriate to the circumstances, and may include examples
such as bipolar disorder, an alteration in mood, and/or depression. An
anxiety disorder may include nervous system disorders such as
irrationality, illogical worry not based on fact, fear, and/or phobia. A
psychotic disorder may include a state of mind in which thinking becomes
irrational and/or disturbed and may include hallucinations, abnormal
perception, mania, dementia, delusions and/or delusional beliefs,
delirium, depression, psychosis personality disorder, personality
changes, and/or disorganized thinking. An eating disorder may include a
compulsion to eat and/or avoid eating that negatively affects physical
and/or mental health. Some examples of an eating disorder may include
anorexia nervosa and bulimia nervosa. A developmental disorder may
include a disorder occurring in a child's development, which may retard
development. Some examples of a developmental disorder may include an
emotional disorder, a cognitive disorder, and/or a mental disorder
accompanied by physical traits, such as Down syndrome. A phobia may
include an irrational, intense, and/or persistent fear of certain
situations, objects, activities, and/or persons. Examples of phobias
include social phobias, arachnophobia, xenophobia, and/or claustrophobia.
A communication disorder may include a disease and/or a condition
partially or totally preventing human communication. Some examples of a
communication disorder may include autism, stuttering, and/or aphasia. A
social disorder may include a condition characterized by a difficulty in
human interaction and/or emotional discomfort in social situations. Some
examples of a social disorder may include stage fright, social anxiety
disorder, and/or shyness. A personality disorder may include a disorder
characterized by pathological trends in personality structure. Some
examples of a personality disorder may include a paranoid personality
disorder, a narcissistic personality disorder, and/or an
obsessive-compulsive personality disorder. In some instances, mental
disorder detector module 642 may include a computer processor.

[0131]Further, operation 1702 illustrates detecting at least one mental
diagnosis associated with at least one individual. For example, as shown
in FIGS. 4 through 8, mental diagnosis detector module 644 can detect at
least one mental diagnosis associated with at least one individual. In a
specific instance, mental diagnosis detector module 644 may detect a
mental diagnosis including a phobia associated with a specific
individual. A mental diagnosis may include identifying a mental disorder
and/or condition by its symptoms. Some examples of a mental diagnosis may
include a mood disorder such as depression, an anxiety disorder such as
PTSD, a behavioral disorder such as ADHD, a personality disorder such as
borderline personality disorder, and/or a phobia. Mental disorders may
include those listed in the Diagnostic and Statistical Manual of Mental
Disorders (DSM). In some instances, mental diagnosis detector module 644
may include a computer processor.

[0132]Further, operation 1704 illustrates detecting at least one of a
depression, a phobia, an anxiety disorder, a personality disorder, a
psychotic disorder, a developmental disorder, a panic disorder, a bipolar
disorder, schizophrenia, an eating disorder, obsessive compulsive
disorder, post traumatic stress disorder, an attentional disorder, a
communication disorder, a social disorder, or a mood disorder. For
example, as shown in FIGS. 4 through 8, mental disorder detector module
646 can detect at least one of a depression, a phobia, an anxiety
disorder, a personality disorder, a psychotic disorder, a developmental
disorder, a panic disorder, a bipolar disorder, schizophrenia, an eating
disorder, obsessive compulsive disorder, post traumatic stress disorder,
an attentional disorder, a communication disorder, a social disorder, or
a mood disorder. In one example, mental disorder detector module 646 may
detect a diagnosis of depression. Depression may include a mental state
characterized by a pessimistic sense of inadequacy and/or a despondent
lack of activity. A phobia may include an irrational, intense, and/or
persistent fear of certain situations, objects, activities, and/or
persons. Some phobias may include social phobias, arachnophobia,
xenophobia, and/or claustrophobia. An anxiety disorder may include
nervous system disorders such as irrationality, illogical worry not based
on fact, fears, and/or phobias. A personality disorder may include a
disorder characterized by pathological trends in personality structure.
Some examples of a personality disorder may include a paranoid
personality disorder, a narcissistic personality disorder, and/or an
obsessive-compulsive personality disorder. A psychotic disorder may
include a state of mind in which thinking becomes irrational and/or
disturbed and may include hallucinations, delusional beliefs, personality
changes, and/or disorganized thinking. A developmental disorder may
include a disorder occurring in a child's development, which may often
retard development. Some examples of a developmental disorder may include
psychological or physical disorders. A panic disorder may include a
condition characterized by recurring panic attacks in combination with
significant behavioral change. A bipolar disorder may include a mood
disorder characterized by the presence of one or more episodes of
abnormally elevated mood, such as Bipolar I disorder, Bipolar II
disorder, cyclothymia, and/or Bipolar-NOS. Schizophrenia may include a
mental illness characterized by impairments in the perception or
expression of reality, most commonly manifesting as auditory
hallucinations, paranoid or bizarre delusions or disorganized speech and
thinking in the context of significant social or occupational
dysfunction. An eating disorder may include a compulsion to eat or avoid
eating, such as anorexia nervosa and/or bulimia nervosa. Obsessive
compulsive disorder may include a psychiatric anxiety disorder
characterized by obsessive, distressing, intrusive thoughts and related
compulsions which attempt to neutralize the obsessions. Post traumatic
stress disorder may include an anxiety disorder that can develop after
exposure to one or more terrifying events in which grave physical harm
occurred or was threatened. An attentional disorder may include a
persistent pattern of inattention and/or hyperactivity, as well as
forgetfulness, poor impulse control or impulsivity, and distractibility,
such as attention-deficit hyperactivity disorder (ADHD). A communication
disorder may include a disease and/or a condition partially or totally
preventing human communication. Some examples of a communication disorder
may include autism, stuttering, and/or aphasia. A social disorder may
include a condition characterized by a difficulty in human interaction
and/or emotional discomfort in social situations. Some examples of a
social disorder may include stage fright, social anxiety disorder, and/or
shyness. A mood disorder may include a condition whereby the prevailing
emotional mood is distorted or inappropriate to the circumstances and may
include examples such as bipolar disorder and/or depression. In some
instances, mental disorder detector module 646 may include a computer
processor.

[0134]Further, operation 1802 illustrates detecting at least one past
mental therapy associated with the at least one individual. For example,
as shown in FIGS. 4 through 8, mental therapy detector module 648 can
detect at least one past mental therapy associated with the at least one
individual. In one instance, mental therapy detector module 648 can
detect an indication of a past mental therapy associated with a specific
individual. A past mental therapy may include a list and/or a record of
at least one mental therapy, such as an anti-depressant medication,
administered to at least one individual. In some instances, mental
therapy detector module 648 may include a computer processor.

[0136]Operation 1902 illustrates detecting the at least one attribute
associated with the at least one individual from a health care provider.
For example, as shown in FIGS. 4 through 8, health care provider detector
module 650 can detect the at least one attribute associated with the at
least one individual from a health care provider. In one example, health
care provider detector module 650 can detect from a health care provider
an attribute associated with a specific individual including a medication
history. A health care provider may include a hospital, a doctor, a
nurse, a medical clinic, a dentist, and/or any provider of preventive,
diagnostic, therapeutic, rehabilitative, maintenance, or palliative care
and/or counseling. A healthcare provider may include a seller and/or
dispenser of prescription drugs or medical devices. In some instances,
health care provider detector module 650 may include a computer
processor.

[0137]Further, operation 1904 illustrates detecting the at least one
attribute associated with the at least one individual from a licensed
health care provider. For example, as shown in FIGS. 4 through 8,
licensed provider detector module 652 can detect the at least one
attribute associated with the at least one individual from a licensed
health care provider. In one instance, licensed provider detector module
652 detects an attribute including a symptom indicating a phobia
associated with a specific individual from a licensed health care
provider. A licensed health care provider may include a person licensed
by a governing authority, such as a state, to provide medical and/or
health care. Some examples of a licensed health care provider may include
a licensed medical doctor or physician, a licensed physician's assistant,
and/or a licensed nurse practitioner. In some instances, licensed
provider detector module 652 may include a computer processor.

[0138]Further, operation 1906 illustrates detecting the at least one
attribute associated with the at least one individual from an alternative
medicine provider. For example, as shown in FIGS. 4 through 8,
alternative medicine provider detector module 654 can detect the at least
one attribute associated with the at least one individual from an
alternative medicine provider. In one instance, alternative medicine
provider detector module 654 may detect a record of bioactive agent
administration associated with a specific individual from an alternative
medicine provider. An alternative medicine provider may include a
provider of folk medicine, herbal medicine, diet fads, homeopathy, faith
healing, new age healing, chiropractic, acupuncture, aromatherapy,
naturopathy, massage, reflexology, hypnotism, and/or music therapy. In
some instances, alternative medicine provider detector module 654 may
include a computer processor.

[0140]Operation 2002 illustrates accepting sensor data from a remote
location. For example, as shown in FIGS. 4 through 8, remote data
accepter module 656 can detect sensor data from a remote location. For
example, remote data accepter module 656 may receive one or more results
from at least one sensor from a remote location. In one embodiment,
remote data accepter module 656 may receive data from a brain sensor from
a remote location, such as from a research hospital in California when
the remote data accepter module 656 is located in Massachusetts. In some
instances, remote data accepter module 656 may include a computer
processor and/or a communication device, for example a network modem and
corresponding network circuitry.

[0141]Operation 2004 illustrates accepting brain sensor data. For example,
as shown in FIGS. 4 through 8, brain sensor data accepter module 658 can
accept brain sensor data. In an embodiment, brain sensor data accepter
module 658 may accept from a brain sensor electrode array. One example of
an electrode array may be found in Flaherty, U.S. Patent Publication No.
2007/0106143, which is incorporated herein by reference. In an
embodiment, brain sensor data accepter module 658 may accept data
detected by an electrode sensor that senses electrical signals generated
by, for example, a patient while imagining movement. In this embodiment,
the sensor may generate electrical signals that may be processed and/or
accepted by, for example, brain sensor data accepter module 658. Some
examples of a brain sensor may include non-invasive sensors, such as
electroencephalogram (EEG) sensors, partially invasive sensors, such as
electrocorticography sensors, and/or invasive sensors, such as implanted
electrodes. A user 140 of a brain sensor may include a patient having a
medical condition, an individual experiencing one or more symptoms, an
asymptomatic individual, or the like. Brain sensor data may include an
indication of physiological impairment, for example for cosmetic
enhancement, pregnancy, or improvement in athletic performance. In an
embodiment, brain sensor data accepter module 658 may accept brain sensor
data from an array of wireless sensors attached to the outside of a
user's 140 head. In this embodiment, the array of wireless sensors may
wirelessly detect electrical signals in the user's 140 brain and
wirelessly relay the information to brain sensor data accepter module
658. The electrical signals produced by the brain may indicate a certain
condition of the brain and/or body, such as physical damage, disability,
and/or cognitive dysfunction, and may additionally indicate the success
of and/or the degree of success of a previously prescribed therapy. In
some instances, brain sensor data accepter module 658 may include a
computer processor.

[0142]Further, operation 2006 illustrates accepting data from at least one
neuroprosthetic. For example, as shown in FIGS. 4 through 8,
neuroprosthetic accepter module 660 can accept data from at least one
neuroprosthetic. A neuroprosthetic may include a device or a series of
devices that may function as a substitute for a motor, sensory, and/or
cognitive modality that may have been damaged and/or may otherwise not
function properly. For example, a neuroprosthetic may include a cochlear
implant. A cochlear implant may serve to substitute the functions
performed by an ear drum. In an embodiment, neuroprosthetic accepter
module 660 may accept data from a cochlear implant. In this embodiment,
the data accepted from the cochlear implant may serve to indicate, for
example, that the cochlear implant is malfunctioning and a surgery for
replacement is needed. In some instances, neuroprosthetic accepter module
660 may include a computer processor.

[0144]Further, operation 2102 illustrates accepting data from at least one
brain-computer interface. For example, as shown in FIGS. 4 through 8,
brain-computer interface accepter module 662 can accept data from at
least one brain-computer interface. A brain-computer interface may
include a direct communication pathway between a brain and an external
device, such as a neuroprosthetic and/or an array of electrodes. In an
embodiment, brain-computer interface accepter module 662 may accept data
from an electrocorticography device. Some brain-computer interface
devices may be intrusive, partially intrusive, and/or non-intrusive. In
some instances, brain-computer interface accepter module 662 may include
a computer processor.

[0145]Further, operation 2104 illustrates accepting data from at least one
invasive brain-computer interface. For example, as shown in FIGS. 4
through 8, invasive accepter module 664 can accept data from at least one
invasive brain-computer interface. An invasive brain-computer interface
device may include a device implanted directly into the grey matter of
the brain during a neurosurgery. In an embodiment, invasive accepter
module 664 may accept data from an array of electrodes implanted into a
user's 140 visual cortex designed to detect electrical signals and/or the
absence of electrical signals and analyzing a user's 140 visual
perception. This may serve to assist in diagnosis of, for example, a
visual disability. Another example of an invasive brain-computer
interface may be found in Boling, U.S. Pat. No. 7,283,856, which is
incorporated herein by reference. In some instances, invasive accepter
module 664 may include a computer processor.

[0147]Further, operation 2202 illustrates accepting data from at least one
partially invasive brain-computer interface. For example, as shown in
FIGS. 4 through 8, partially invasive accepter module 666 can accept data
from at least one partially invasive brain-computer interface. A
partially invasive brain-computer interface may include a device
implanted inside a person's skull but outside the brain. Some examples of
a partially invasive brain-computer interface may include an
electrocorticography device and/or a light reactive imaging device. In an
embodiment, partially invasive accepter module 666 may accept data from
at least one partially invasive brain-computer interface, such as an
electrode implanted between an individual's brain and skull. In some
instances, partially invasive accepter module 666 may include a computer
processor.

[0148]Further, operation 2204 illustrates accepting data from at least one
electrocorticography electrode. For example, as shown in FIGS. 4 through
8, electrocorticography accepter module 668 can accept data from at least
one electrocorticography electrode. An electrocorticography device may
include at least one electrode configured to measure electrical activity
of the brain where, for example, the electrodes are embedded in a thin
plastic pad that is placed above the cortex and beneath the dura matter.
In an embodiment, electrocorticography accepter module 668 may accept
data from at least one electrocorticography electrode configured to
measure electrical signals in the brain of a patient that suffers from
epilepsy. In this example, measuring the electrical signals may assist in
determining the timing and/or intensity of an epileptic seizure and may
help determine a suitable therapy for the patient. Another example of an
electrocorticography device may be found in Leuthardt, U.S. Pat. No.
7,120,486, which is incorporated herein by reference. In some instances,
electrocorticography accepter module 668 may include a computer processor
and/or accepting circuitry, such as a modem.

[0150]Further, operation 2302 illustrates accepting data from at least one
non-invasive brain-computer interface. For example, as shown in FIGS. 4
through 8, non-invasive interface accepter module 670 can accept data
from at least one non-invasive brain-computer interface. A non-invasive
brain-computer interface may include a device that is able to measure
signals from the brain without substantially interfering with and/or
disturbing body tissue. In one embodiment, non-invasive interface
accepter module 670 may accept information from wireless brain sensors
that are placed on an individual's head. Another example of a
non-invasive brain-computer interface may include an
electroencephalography sensor. In some instances, non-invasive interface
accepter module 670 may include a computer processor.

[0151]Further, operation 2304 illustrates accepting data from at least one
wireless brain sensor. For example, as shown in FIGS. 4 through 8,
wireless sensor accepter module 672 can accept data from at least one
wireless brain sensor. In an embodiment, wireless sensor accepter module
672 may accept data from an array of brain sensors placed on the outside
of an individual's head. In this embodiment, the array of brain sensors
may detect electromagnetic waves created by neurons. The wireless brain
sensor may be wirelessly connected to the wireless sensor accepter module
672. Additional examples of a wireless brain sensor may include Fish,
U.S. Pat. No. 6,155,974, and Najafi, et al., U.S. Patent Publication No.
2009/0105557, both of which are incorporated herein by reference. In some
instances, wireless sensor accepter module 672 may include a computer
processor.

[0154]Electroencephalography may include measuring the electrical activity
of the brain by recording from electrodes placed on the scalp or, in
special cases, subdurally, or in the cerebral cortex, or from remote
sensors. The resulting traces are known as an electroencephalogram (EEG)
and represent a summation of post-synaptic potentials from a large number
of neurons. EEG is most sensitive to a particular set of post-synaptic
potentials: those which are generated in superficial layers of the
cortex, on the crests of gyri directly abutting the skull and radial to
the skull. Dendrites that are deeper in the cortex, inside sulci, are in
midline or deep structures (such as the cingulate gyrus or hippocampus)
or that produce currents that are tangential to the skull make a smaller
contribution to the EEG signal.

[0155]One application of EEG is event-related potential (ERP) analysis. An
ERP is any measured brain response that is directly the result of a
thought or perception. ERPs can be reliably measured using
electroencephalography (EEG), a procedure that measures electrical
activity of the brain, typically through the skull and scalp. As the EEG
reflects thousands of simultaneously ongoing brain processes, the brain
response to a certain stimulus or event of interest is usually not
visible in the EEG. One of the most robust features of the ERP response
is a response to unpredictable stimuli. This response is known as the
P300 (P3) and manifests as a positive deflection in voltage approximately
300 milliseconds after the stimulus is presented.

[0156]A two-channel wireless brain wave monitoring system powered by a
thermo-electric generator has been developed by IMEC (Interuniversity
Microelectronics Centre, Leuven, Belgium). This device uses the body heat
dissipated naturally from the forehead as a means to generate its
electrical power. The wearable EEG system operates autonomously with no
need to change or recharge batteries. The EEG monitor prototype is
wearable and integrated into a headband where it consumes 0.8 milliwatts.
A digital signal processing block encodes extracted EEG data, which is
sent to a PC via a 2.4-GHz wireless radio link. The thermoelectric
generator is mounted on the forehead and converts the heat flow between
the skin and air into electrical power. The generator is composed of 10
thermoelectric units interconnected in a flexible way. At room
temperature, the generated power is about 2 to 2.5-mW or 0.03-mW per
square centimeter, which is the theoretical limit of power generation
from the human skin. Such a device is proposed to associate emotion with
EEG signals. See Clarke, "IMEC has a brain wave: feed EEG emotion back
into games," EE Times online, http://www.eetimes.eu/design/202801063
(Nov. 1, 2007).

[0157]Computed axial tomography may include medical imaging employing
tomography and digital geometry processing for generating a
three-dimensional image of the inside of an object from a large series of
two-dimensional X-ray images taken around a single axis of rotation.
Positron emission tomography may include a nuclear medicine imaging
technique, which produces a three-dimensional image and/or map of at
least one functional process in the body. The system detects pairs of
gamma rays emitted indirectly by a positron-emitting radionuclide (a
tracer), which is introduced into the body on a biologically active
molecule. Images of tracer concentration in 3-dimensional space within
the body may then be reconstructed by computer analysis. Magnetic
resonance imaging may include a medical imaging technique using a
magnetic field to align the nuclear magnetization of hydrogen atoms in
water in the body, resulting in an image of the body. Functional magnetic
resonance imaging may include and imaging method for measuring
haemodynamic response related to neural activity in the brain or spinal
cord. Functional near-infrared imaging (fNIR) may include a spectroscopic
neuro-imaging method for measuring the level of neuronal activity in the
brain. Functional near-infrared imaging (fNIR) is based on neuro-vascular
coupling, or the relationship between metabolic activity and oxygen level
(oxygenated hemoglobin) in feeding blood vessels.

[0158]Magnetoencephalography includes measuring the magnetic fields
produced by electrical activity in the brain using magnetometers such as
superconducting quantum interference devices (SQUIDs) or other devices.
Smaller magnetometers are in development, including a mini-magnetometer
that uses a single milliwatt infrared laser to excite rubidium in the
context of an applied perpendicular magnetic field. The amount of laser
light absorbed by the rubidium atoms varies predictably with the magnetic
field, providing a reference scale for measuring the field. The stronger
the magnetic field, the more light is absorbed. Such a system is
currently sensitive to the 70 fT range, and is expected to increase in
sensitivity to the 10 fT range. See Physorg.com, "New mini-sensor may
have biomedical and security applications," Nov. 1, 2007,
http://www.physorg.com/news113151078.html, which is incorporated herein
by reference.

[0160]Further, operation 2502 illustrates accepting at least one brain
activity surrogate marker. For example, as shown in FIGS. 4 through 8,
marker accepter module 676 can accept at least one brain activity
surrogate marker. In some instances, marker accepter module 676 may
include a computer processor and/or medical instrumentality configured to
measure a surrogate marker, such as a stethoscope, a face recognition
system, and/or a sphygmomanometer. Brain activity surrogate markers may
include indicators of attention, approval, disapproval, recognition,
cognition, memory, trust, or the like in response to a stimulus, other
than measurement of brain activity associated with the stimulus. Some
examples of surrogate markers may include a skin response to a stimulus;
a face pattern indicative of approval, disapproval, or emotional state;
eye movements or pupil movements indicating visual attention to an
object; voice stress patterns indicative of a mental state, or the like.
Surrogate markers may be used in conjunction with brain activity
measurements for higher confidence in a predictive or interpretational
outcome. For example, brain activation of the caudate nucleus in
combination with calm voice patterns may increase confidence in a
predictor of trust between a subject and a stimulus. Additional
discussion regarding surrogate markers may be found in Cohn, J. N.,
Introduction to Surrogate Markers, CIRCULATION 109: IV20-21, American
Heart Association, (2004), which is incorporated herein by reference.

[0161]For example, emotion links to cognition, motivation, memory,
consciousness, and learning and developmental systems. Affective
communication depends on complex, rule-based systems with multiple
channels and redundancy built into the exchange system, in order to
compensate if one channel fails. Channels can include all five senses:
for example, increased heart-rate or sweating may show tension or
agitation and can be heard, seen, touched, smelt or tasted. Emotional
exchanges may be visible displays of body tension or movement, gestures,
posture, facial expressions or use of personal space; or audible displays
such as tone of voice, choice of pitch contour, choice of words, speech
rate, etc. Humans also use touch, smell, adornment, fashion,
architecture, mass media, and consumer products to communicate our
emotional state. Universals of emotion that cross cultural boundaries
have been identified, and cultural differences have also been identified.
For example `love` is generally categorized as a positive emotion in
Western societies, but in certain Eastern cultures there is also a
concept for `sad love.` Accordingly, universal emotional triggers may be
used to transcend cultural barriers.

[0162]When communicating with computers, people often treat new media as
if they were dealing with real people. They often follow complex social
rules for interaction and modify their communication to suit their
perceived conversation partner. Much research has focused on the use of
facial actions and ways of coding them. Speech recognition systems have
also attracted attention as they grow in capability and reliability, and
can recognize both verbal messages conveyed by spoken words, and non
verbal messages, such as those conveyed by pitch contours.

[0163]System responses and means of expressing emotions also vary.
Innovative prototypes are emerging designed to respond indirectly, so the
user is relatively unaware of the response: for example by adaptation of
material, such as changing pace or simplifying or expanding content.
Other systems use text, voice technology, visual agents, or avatars to
communicate. See Axelrod et al., "Smoke and Mirrors: Gathering User
Requirements for Emerging Affective Systems," 26th Int. Conf. Information
Technology Interfaces/TI 2004, Jun. 7-10, 2004, Cavtat, Croatia, pp.
323-328, which is incorporated herein by reference.

[0164]Further, operation 2504 illustrates accepting at least one of iris
dilation or constriction, gaze tracking, skin response, or voice
response. For example, as shown in FIGS. 4 through 8, response accepter
module 678 can accept at least one of iris dilation or constriction, gaze
tracking, skin response, or voice response. In some instances, response
accepter module 678 may include a computer processor and/or medical
instrumentality, such as a stethoscope and/or a sphygmomanometer. In one
embodiment, response accepter module 678 may record changes in the
movement of an individual's iris (with corresponding changes in the size
of the pupil) before, during, and/or after administration of a bioactive
agent and/or an artificial sensory experience. Such measurements of
physiologic activity that indicate brain activity and/or mental state may
be carried out at a time that is proximate to administration of a
bioactive agent and/or an artificial sensory experience.

[0165]In one embodiment, response accepter module 678 may measure and/or
record gaze tracking. In some instances, response accepter module 678 may
include a camera that can monitor a subject's eye movements in order to
determine whether the subject looks at a presented characteristic, for
example, during a certain time period. For example, a camera may include
a smart camera that can capture images, process them and issue control
commands within a millisecond time frame. Such smart cameras are
commercially available (e.g., Hamamatsu's Intelligent Vision System;
http://jp.hamamatsu.com/en/product_info/index.html). Such image capture
systems may include dedicated processing elements for each pixel image
sensor. Other camera systems may include, for example, a pair of infrared
charge coupled device cameras to continuously monitor pupil size and
position as a user watches a visual target moving forward and backward.
This can provide real-time data relating to pupil accommodation relative
to objects on, for example, a user interface, such as a display. (e.g.,
http://jp.hamamatsu.com/en/rd/publication/scientific_american/common/pdf/-
scientific--0608.pdf).

[0166]Eye movement and/or iris movement may also be measured by
video-based eye trackers. In these systems, a camera focuses on one or
both eyes and records eye movement as the viewer looks at a stimulus.
Contrast may be used to locate the center of the pupil, and infrared and
near-infrared non-collumnated light may be used to create a corneal
reflection. The vector between these two features can be used to compute
gaze intersection with a surface after a calibration for an individual.

[0167]In one embodiment, response accepter module 678 may measure and/or
record skin response. Brain activity may be determined by detection of a
skin response associated with a stimulus. One skin response that may
correlate with mental state and/or brain activity is galvanic skin
response (GSR), also known as electrodermal response (EDR),
psychogalvanic reflex (PGR), or skin conductance response (SCR). This is
a change in the electrical resistance of the skin. There is a
relationship between sympathetic nerve activity and emotional arousal,
although one may not be able to identify the specific emotion being
elicited. The GSR is highly sensitive to emotions in some people. Fear,
anger, startle response, orienting response, and sexual feelings are all
among the emotions which may produce similar GSR responses. GSR is
typically measured using electrodes to measure skin electrical signals.

[0168]For example, an Ultimate Game study measured skin-conductance
responses as a surrogate marker or autonomic index for affective state,
and found higher skin conductance activity for unfair offers, and as with
insular activation in the brain, this measure discriminated between
acceptances and rejections of these offers. See Sanfey, "Social
Decision-Making: Insights from Game Theory and Neuroscience," Science,
vol. 318, pp. 598-601 (26 Oct. 2007), which is incorporated herein by
reference. Other skin responses may include flushing, blushing, goose
bumps, sweating, or the like.

[0169]In one embodiment, response accepter module 678 may measure and/or
record voice response. Voice response may include speech captured by a
microphone during presentation of a characteristic. Speech or voice can
be measured, for example, by examining voice, song, and/or other vocal
utterances of a subject before, during, and/or after administration of a
bioactive agent and/or an artificial sensory experience to an individual.
Such measurements may include, for example, as discussed above, layered
voice analysis, voice stress analysis, or the like.

[0170]The reaction of an individual to an administered bioactive agent
and/or an artificial sensory experience, such as an event in a virtual
world may be a recognizable vocal exclamation such as "Wow, that's nice!"
that may be detectable by a response accepter module 678, such as a
microphone monitoring the subject while being administered an artificial
sensory experience. A response accepter module 678 may include a voice
response module and/or a speech recognition function, such as a software
program or computational device that can identify and/or record an
utterance of a subject as speech or voice data.

[0172]Operation 2602 illustrates accepting at least one of oxygen sensor
data, electricity sensor data, chemical sensor data, or temperature
sensor data. For example, as shown in FIGS. 4 through 8, physiological
data accepter module 680 can accept at least one of oxygen sensor data,
electricity sensor data, chemical sensor data, or temperature sensor
data. In an embodiment, physiological data accepter module 680 may accept
temperature sensor data from an infrared thermometer. One example of an
oxygen sensor may include a pulse oximeter. Another example of an oxygen
sensor may be found in Milstein et al., U.S. Pat. No. 5,106,482. Some
examples of an electricity sensor may include an electroencephalography
sensor and/or a piezoelectric ultrasound transducer. An additional
example of an electricity sensor may include the bio-electric sensor
found in Shahinpoor et al., U.S. Pat. No. 6,829,499, which is
incorporated herein by reference. A chemical sensor may include, for
example, a pH meter and/or a blood glucose sensor. An additional chemical
sensor system may be found in Darrow et al., U.S. Pat. No. 6,480,730,
which is incorporated herein by reference. Some examples of a temperature
sensor may include a thermocouple and/or a thermometer. An additional
example of a temperature system may be found in Takaki, U.S. Pat. No.
6,019,507, which is incorporated herein by reference. In some instances,
physiological data accepter module 680 may include a computer processor
and/or connecting circuitry, such as wired connections or a keyboard.

[0173]Operation 2604 illustrates accepting at least one of blood glucose
sensor data, blood pressure sensor data, blood alcohol sensor data, or
heart rhythm sensor data. For example, as shown in FIGS. 4 through 8,
blood sensor data accepter module 682 can accept at least one of blood
glucose sensor data, blood pressure sensor data, blood alcohol sensor
data, or heart rhythm sensor data. In an embodiment, blood sensor data
accepter module 682 may accept blood glucose sensor data. One example of
a blood glucose meter may include the ACCU-CHEK Aviva Blood Glucose Meter
available from Roche, Basel, Switzerland. An example of a blood pressure
sensor may include a blood pressure cuff and/or a sphygmomanometer. An
example of a blood alcohol sensor may include a breathalyzer such as the
BACtrack S50 Breathalyzer, available from KHN Solutions LLC, San
Francisco, Calif. An example of a heart rhythm sensor may include an EKG
based heart rate monitor, such as the monitor found in Lo et al., U.S.
Pat. No. 5,738,104, or the heart sound sensor found in Anderson et al.,
U.S. Patent Publication No. 2009/0030334, both of which are incorporated
herein by reference. In some instances, blood sensor data accepter module
682 may include a computer processor.

[0175]Operation 2702 illustrates presenting a sequence of at least one of
diagnostic options or treatment options. For example, as shown in FIGS. 4
through 8, sequence presenter module 684 can present a sequence of at
least one of diagnostic options or treatment options. In one embodiment,
sequence presenter module 684 can present a sequence of treatment options
for obesity. A flow diagram may be determined and presented based on
accepted weight sensor data, including a sequence of examinations and
eventual treatment options. The list of sequential options may include
service providers where appropriate, such as a weight specialist consult
and a surgeon consult. This may serve to identify for the user potential
service providers who may be required for providing care. In some
instances, sequence presenter module 684 may include a computer
processor.

[0176]Operation 2704 illustrates presenting the set of health care options
in a decision-tree format. For example, as shown in FIGS. 4 through 8,
format presenter module 686 can present the set of health care options in
a decision-tree format. In one embodiment, format presenter module 686
may present options to address "epilepsy" as a health-related status. In
this embodiment, two treatment paths may be depicted (e.g.,
pharmaceutical therapy (Path A) and surgery (Path B)). Such a depiction
may show the treatment paths from the general to the specific, including
the kinds of service provider available for each path, specific
interventions typically offered by the service providers, such as types
and specific drugs available by prescription in the case of Path A. In
the example of Path A, the information provided by format presenter
module 686 can inform a user considering pharmaceutical therapy for
epilepsy. That user may use the information to contact a physician with
questions about the various drugs listed/approved for treating epilepsy.
In some embodiments, further information may be provided, for example,
costs associated with various treatments, side effects associated with
various treatments, success rates, or the like. In one embodiment, format
presenter module 686 may determine a decision tree showing medical
treatments. Other examples of medical treatment decision trees can be
found in U.S. Pat. No. 6,807,531, which is incorporated herein in its
entirety. In some instances, format presenter module 686 may include a
computer processor.

[0177]Evaluation of health services options is discussed in depth in
Goodman, Clifford S., "Introduction to Health Care Technology
Assessment," available at
http://www.nlm.nih.gov/nichsr/hta101/ta101_c1.html, (January 2004), which
is incorporated by reference herein in its entirety. An example of
evaluation of health services options including a specific decision tree
can be found in "Cancer in Scotland: Radiotherapy Activity Planning for
Scotland 2011-2015," available at
http://www.scotland.gov.uk/Publications/2006/01/24131719/28, (2006),
which is incorporated by reference herein in its entirety. An example of
a decision tree in the alternative medicine context can be found at
http://cam.utmb.edu/curriculum/cam-decision-tree.asp and in Frenkel et
al., "An approach for integrating complementary-alternative medicine into
primary care," Fam. Pract., 20(3), pp. 324-332 (2003).

[0178]Operation 2706 illustrates presenting the set of health care options
with at least one of testing side effect data, treatment side effect
data, testing outcome data, or treatment outcome data. For example, as
shown in FIGS. 4 through 8, testing data presenter module 688 can present
the set of health care options with at least one of testing side effect
data, treatment side effect data, or testing outcome data, treatment
outcome data. In one embodiment, testing data presenter module 688 can
present efficacy and/or side effect data for a given treatment option. In
this embodiment, for each surgery option shown, outcome and efficacy data
may be provided as well as complication and side effect data. In this
embodiment, efficacy data may include improvement in long-term mortality
rates, reduction in comorbidities, the rate of occurrence of epileptic
episodes, or the like. Complication and side effect data may include
incidence of infection, nausea, pain, or the like. In some instances,
testing data presenter module 688 may include a computer processor.

[0180]Operation 2802 illustrates presenting at least one of a specified
number of health care options for a given stage of testing or treatment,
a specified number of branch points for a given course of testing or
treatment, or a specified number of decision levels for a given course of
testing or treatment. For example, as shown in FIGS. 4 through 8, number
presenter module 690 can present at least one of a specified number of
health care options for a given stage of testing or treatment, a
specified number of branch points for a given course of testing or
treatment, or a specified number of decision levels for a given course of
testing or treatment. In one embodiment, number presenter module 690 may
present a maximum of two treatment options for a given stage of treatment
(e.g., Paths A and B in the above example. In another embodiment, one
testing/treatment option may be shown at each stage of testing/treatment.
In this embodiment, several options are collapsed into one option box.
For example, a surgery option box may include several options such as
resection of lesions, palliative surgery, and hemispherectomy. These
additional options may be shown if the user so chooses. Benefits of
limiting the number of options at each stage include making the decision
tree more manageable to digest and understand in terms of presenting a
big picture of a prospective course of testing and/or treatment.
Conversely, expanding the number of options provides more information
about the options available at each stage. In some instances, number
presenter module 690 may include a computer processor.

[0182]Operation 2902 illustrates presenting the set of health care options
at least partially based on at least one user preference. For example, as
shown in FIGS. 4 through 8, preference presenter module 692 can present
the set of health care options at least partially based on at least one
user preference. In one embodiment, preference presenter module 692 may
present, for example, a course of testing and/or treatment that takes
into account one or more preferences or sensitivities of the individual,
such as "treatments other than surgery," "local treatment options,"
"non-narcotic treatment options," or the like. In some instances,
preference presenter module 692 may include a computer processor.

[0183]Further, operation 2904 illustrates presenting the set of health
care options based on accepting sensor data and based on at least one
type of treatment. For example, as shown in FIGS. 4 through 8, accepted
data presenter module 694 can present the set of health care options
based on accepting sensor data and based on at least one type of
treatment. In one embodiment, accepted data presenter module 694 may
present a set of health service options for an individual based on brain
sensor data that indicates a likelihood of epilepsy and an individual's
preference of treatment type. In this example, a user may specify a
preference that excludes alternative medicine options, and/or that
includes surgery options. In some instances, accepted data presenter
module 694 may include a computer processor.

[0184]Further, operation 2906 illustrates presenting the set of health
care options based on at least one of an invasive treatment, a
non-invasive treatment, a treatment type having a specified risk
attribute, a treatment type approved by a third party, or a treatment
associated with a specific substance. For example, as shown in FIGS. 4
through 8, treatment presenter module 696 can present the set of health
care options based on at least one of an invasive treatment, a
non-invasive treatment, a treatment type having a specified risk
attribute, a treatment type approved by a third party, or a treatment
associated with a specific substance. In one embodiment, treatment
presenter module 696 may access user preference data in order to present
a health service option for the individual. For example, a user
preference against surgery as an option for epilepsy may lead to a
determination of Paths A and B in the above example. In another example,
treatment presenter module 696 may access a standard of care database in
order to determine health care options for treating epilepsy that are
approved by, for example, the American Medical Association as a third
party. In some instances, treatment presenter module 696 may include a
computer processor.

[0186]Further, operation 3002 illustrates presenting the set of health
care options based on at least one of a location preference or a time
frame preference. For example, as shown in FIGS. 4 through 8, location
preference module 698 can present the set of health care options based on
at least one of a location preference or a time frame preference. In one
embodiment, location preference module 698 may present at least one
health service option based on brain sensor data indicating a likelihood
of epileptic seizure and a location such as "Miami-Dade County, Fla." A
database of relevant service providers may contain, inter alia, location
information allowing location preference module 698 to present or
determine, in this example, only relevant surgeons located in Miami-Dade
County, Fla. Additionally, location preference module 698 may filter out
database results that include surgeons with, for example, less than five
years of experience in practice and/or located outside of a specified
geographic area, in some cases resulting in zero options being listed for
a given therapy. In a case where no options are returned, other treatment
options may be selected and a new search carried out. In some instances,
location preference module 698 may include a computer processor.

[0187]Further, operation 3004 illustrates presenting the set of health
care options based on at least one recognized health care provider. For
example, as shown in FIGS. 4 through 8, recognized provider presenter
module 700 can present the set of health care options based on at least
one recognized health care provider. In one embodiment, recognized
provider presenter module 700 may present a surgeon as a health service
option based on the key phrase "epileptic surgery" and certified by the
"American Board of Surgery" as the recognized health care provider. Some
other examples of recognized health care providers may include ranked
doctors, ranked hospitals, health care providers having an award for
quality of care, or the like. In some instances, recognized provider
presenter module 700 may include a computer processor.

[0189]Further, operation 3102 illustrates presenting the set of health
care options based on at least one health care provider that is
compatible with a payment capacity of the user or an individual. For
example, as shown in FIGS. 4 through 8, payment presenter module 702 can
present the set of health care options based on at least one health care
provider that is compatible with a payment capacity of the user or an
individual. In one embodiment, payment presenter module 702 may present
treatment options based on the key phrase "Alzheimer's" (determined by
utilizing brain sensor data) and "Medicaid" as the payment capacity of
the individual. In this example, treatment options available for payment
with Medicaid may be determined and presented to the user. These
treatment options will be limited to those approved by the United States
Food and Drug Administration, while others, such as Aricept®, may be
omitted as incompatible with Medicaid coverage. Conversely, if the
payment capacity for the individual is high, off-label treatments and
those with experimental status may be included as treatment options.
Examples of other payment capacities include specific private insurance
plans such as Premera, Blue Cross/Blue Shield, or the like. Other
examples include Medicare, fee-for-service, point-of-service, preferred
provider organizations, or health maintenance organizations. In some
instances, payment presenter module 702 may include a computer processor.

[0190]Further, operation 3104 illustrates presenting the set of health
care options based on at least one health care provider that accepts at
least one of Medicare, Medicaid, uninsured patients, workers'
compensation, or supplemental health insurance. For example, as shown in
FIGS. 4 through 8, insurance presenter module 704 can present the set of
health care options based on at least one health care provider that
accepts at least one of Medicare, Medicaid, uninsured patients, workers'
compensation, or supplemental health insurance. In one embodiment,
insurance presenter module 704 may present at least one health service
option based on an accepted key phrase such as "Cerebral palsy" and "no
insurance" as indications of at least one health-related status of an
individual. In this example, insurance presenter module 704 may determine
care options that are available to an uninsured individual, such as
services provided by Denver Health, Denver's public health system, or the
Seton System in Central Texas. In some instances, insurance presenter
module 704 may include a computer processor.

[0192]Further, operation 3202 illustrates presenting the set of health
care options based on at least one health care provider able to see the
user or an individual within a specified time period. For example, as
shown in FIGS. 4 through 8, time period presenter module 706 can present
the set of health care options based on at least one health care provider
able to see the user or an individual within a specified time period. In
one embodiment, time period presenter module 706 may present information
about home care nurses who have immediate availability according to the
individual's needs and may present a set of available home care nurses in
response to accepting "hospice care" and "immediate availability" as
accepted indications of health-related status of an individual. In some
instances, time period presenter module 706 may include a computer
processor.

[0194]Further, operation 3302 illustrates presenting the set of health
care options based on at least one of a health care provider reported to
have the best clinical outcomes for a given diagnosis, a health care
provider giving the lowest-cost care for a given diagnosis, a health care
provider having a highly-rated bedside manner, a health care provider
recommended by her peers, or a health care provider located within a
specific geographical proximity to the user or an individual. For
example, as shown in FIGS. 4 through 8, provider result presenter module
708 can present the set of health care options based on at least one of a
health care provider reported to have the best clinical outcomes for a
given diagnosis, a health care provider giving the lowest-cost care for a
given diagnosis, a health care provider having a highly-rated bedside
manner, a health care provider recommended by her peers, or a health care
provider located within a specific geographical proximity to the user or
an individual. In one embodiment, provider result presenter module 708
may access data relating to hospital rankings for neural disorders, for
example the U.S. News and World Report Hospital rankings and present the
hospital rankings to a user. In this example, online rankings may show
the Mayo Clinic in Rochester, Minn., Mass. General Hospital in Boston,
Mass., and Johns Hopkins Hospital in Baltimore, Md. as the top three
hospitals for treating neurology disorders in the United States. In some
instances, provider result presenter module 708 may include a computer
processor.

[0195]Further, operation 3304 illustrates presenting the set of health
care options based on a health care provider sharing at least one of a
common gender, a common religion, a common race, or a common sexual
orientation as the user or an individual. For example, as shown in FIGS.
4 through 8, commonality presenter module 710 can present the set of
health care options based on a health care provider sharing at least one
of a common gender, a common religion, a common race, or a common sexual
orientation as the user or an individual. In an embodiment, commonality
presenter module 710 can present a set of physicians based on a user's
preference for a Jewish doctor based at least in part on the user's
religious beliefs as a Jew. In some instances, commonality presenter
module 710 may include a computer processor.

[0198]Operation 3404 illustrates presenting at least one of treatment by a
medical doctor, treatment by a naturopathic doctor, treatment by an
acupuncturist, treatment by an herbalist, self-treatment, taking no
action for a period of time, or taking no action until a specified
indicator crosses a threshold. For example, as shown in FIGS. 4 through
8, treatment presenter module 714 can present at least one of treatment
by a medical doctor, treatment by a naturopathic doctor, treatment by an
acupuncturist, treatment by an herbalist, self-treatment, taking no
action for a period of time, or taking no action until a specified
indicator crosses a threshold. In one embodiment, treatment presenter
module 714 may accept "narcolepsy" as an indication of health-related
status and determine various health service options, such as treatment by
an acupuncturist. In this embodiment, treatment presenter module 714 may
present a list of acupuncturists with experience in treating narcolepsy.
Virtually any combination of available testing/treatment options may be
presented. Additionally, testing/treatment options may be narrowed by
user preference. In some instances, treatment presenter module 714 may
include a computer processor.

[0200]Operation 3502 illustrates presenting at least one of a diagnosis
option set or a treatment option set. For example, as shown in FIGS. 4
through 8, option set presenter module 716 can presenting at least one of
a diagnosis option set or a treatment option set. In one embodiment,
diagnosis or testing options may be determined and presented as initial
steps in a decision flow diagram, followed by treatment options. In this
embodiment, option set presenter module 716 may present the diagnosis
and/or treatment options as a decision flow diagram as well as other
presentation formats. In some instances, option set presenter module 716
may include a computer processor.

[0201]Operation 3504 illustrates presenting the set of health care options
at least partly based on at least one of a standard of care, an expert
opinion, an insurance company evaluation, or research data. For example,
as shown in FIGS. 4 through 8, standard presenter module 718 can present
the set of health care options at least partly based on at least one of a
standard of care, an expert opinion, an insurance company evaluation, or
research data. In one embodiment, standard presenter module 718 may
present a set of health service options based on a standard of care
database. The standard of care database may include information, such as
treatment options that are currently recommended by the medical community
and/or approved by one or more insurance companies. In some instances,
standard presenter module 718 may include a computer processor.

[0202]Operation 3506 illustrates presenting at least one of a list of
diagnosticians, a list of clinicians, a list of therapists, a list of
dentists, a list of optometrists, a list of pharmacists, a list of
nurses, a list of chiropractors, or a list of alternative medicine
practitioners. For example, as shown in FIGS. 4 through 8, list presenter
module 720 can present at least one of a list of diagnosticians, a list
of clinicians, a list of therapists, a list of dentists, a list of
optometrists, a list of pharmacists, a list of nurses, a list of
chiropractors, or a list of alternative medicine practitioners. In one
embodiment, list presenter module 720 can, based on accepted brain sensor
data, access a service provider database to determine a list of
clinicians (e.g., surgeons). In this embodiment, list presenter module
720 can present a list of clinicians experienced in treating neurological
disorders indicated by the accepted brain sensor data. In another
example, list presenter module 720 can access a service provider database
to provide a list of physicians who are pain specialists and a list of
acupuncturists in response to receiving "head pain" as an indication of
health-related status. In some instances, list presenter module 720 may
include a computer processor.

[0204]Operation 3602 illustrates presenting at least one list of treatment
centers. For example, as shown in FIGS. 4 through 8, center presenter
module 722 can present at least one list of treatment centers. In one
embodiment, center presenter module 722 may present a list of hospitals
that perform a given medical procedure to a user at least partially based
on data accepted from an array of brain sensors. In some instances,
center presenter module 722 may include a computer processor.

[0205]Further, operation 3604 illustrates presenting at least one of a
list of clinics, a list of hospitals, a list of medical offices, or a
list of alternative medicine practice offices. For example, as shown in
FIGS. 4 through 8, medical office presenter module 724 can present at
least one of a list of clinics, a list of hospitals, a list of medical
offices, or a list of alternative medicine practice offices. In one
embodiment, medical office presenter module 724 may present a list of
dementia treatment clinics for an individual in need of dementia-related
health service options. In another example, medical office presenter
module 724 may determine a list of epilepsy clinics. In some instances,
medical office presenter module 724 may include a computer processor.

[0207]Operation 3702 illustrates using at least one third party reference
to present the set of health care options. For example, as shown in FIGS.
4 through 8, third party user module 726 can use at least one third party
reference to present the set of health care options. In one embodiment,
third party user module 726 may use a Physicians' Desk Reference (PDR)
database to determine and then present, for example, a set of
health-related services options for an individual with traumatic brain
injury. In this example, third party user module 726 may use a PDR
neurology database to retrieve health-related services options for a
patient with traumatic brain injury. In some instances, third party user
module 726 may include a computer processor.

[0208]Further, operation 3704 illustrates using at least one of a search
engine, a Deep Web search program, a web crawler, an online database, or
an online directory to present the set of health care options. For
example, as shown in FIGS. 4 through 8, computer user module 728 can use
at least one of a search engine, a Deep Web search program, a web
crawler, an online database, or an online directory to present the set of
health care options. In one embodiment, computer user module 728 may use
a web crawler to identify a suitable online database, and then a
subsequent search function to extract specific data from the online
database. For example, if computer user module 728 accepts "Tourette
syndrome" as an indication of at least one health-related status of an
individual, it may initiate a search of the web for medical research
databases containing Tourette syndrome treatment information. A possible
result of this search is the medical research database "PubMed." Computer
user module 728 next may search the PubMed database for "Tourette
syndrome" in order to determine specific treatment information as the at
least one health service option. In some instances, computer user module
728 may include a computer processor.

[0210]Operation 3802 illustrates detecting an individual's input regarding
a series of epileptic seizures, accepting data from an array of brain
sensor electrodes, and presenting a set of epilepsy medications and a set
of physicians that specialize in treating epilepsy based on accepting the
individual's input regarding a series of epileptic seizures and based on
accepting the data from the array of brain sensor electrodes. For
example, as shown in FIGS. 4 through 8, attribute accepter module 602,
data accepter module 604, and presenter module 606 can accept an
individual's input regarding a series of epileptic seizures, accept data
from an array of brain sensor electrodes, and present a set of epilepsy
medications and a set of physicians that specialize in treating epilepsy
based on accepting the individual's input regarding a series of epileptic
seizures and based on accepting the data from the array of brain sensor
electrodes. In some instances, attribute accepter module 602 may include
a computer processor. In some instances, data accepter module 604 may
include a computer processor. In some instances, presenter module 606 may
include a computer processor.

[0211]FIG. 39 illustrates a partial view of an example computer program
product 3900 that includes a computer program 3904 for executing a
computer process on a computing device. An embodiment of the example
computer program product 3900 is provided using a signal-bearing medium
3902, and may include one or more instructions for detecting an
indication of at least one attribute of an individual, one or more
instructions for accepting sensor data about the individual, and one or
more instructions for presenting a set of health care options at least
partially based on the detecting an indication of at least one attribute
of the individual and the accepting sensor data about the individual. The
one or more instructions may be, for example, computer executable and/or
logic-implemented instructions. In one implementation, the signal-bearing
medium 3902 may include a computer-readable medium 3906. In one
implementation, the signal bearing medium 3902 may include a recordable
medium 3908. In one implementation, the signal bearing medium 3902 may
include a communications medium 3910.

[0212]FIG. 40 illustrates an example system 4000 in which embodiments may
be implemented. The system 4000 includes a computing system environment.
The system 4000 also illustrates the user 118 using a device 4004, which
is optionally shown as being in communication with a computing device
4002 by way of an optional coupling 4006. The optional coupling 4006 may
represent a local, wide-area, or peer-to-peer network, or may represent a
bus that is internal to a computing device (e.g., in example embodiments
in which the computing device 4002 is contained in whole or in part
within the device 4004). A storage medium 4008 may be any computer
storage media.

[0213]The computing device 4002 includes computer-executable instructions
4010 that when executed on the computing device 4002 cause the computing
device 4002 to detect an indication of at least one attribute of an
individual, accept sensor data about the individual, and present a set of
health care options at least partially based on the accepting an
indication of at least one attribute of the individual and the accepting
sensor data about the individual. As referenced above and as shown in
FIG. 40, in some examples, the computing device 4002 may optionally be
contained in whole or in part within the device 4004.

[0214]In FIG. 40, then, the system 4000 includes at least one computing
device (e.g., 4002 and/or 4004). The computer-executable instructions
4010 may be executed on one or more of the at least one computing device.
For example, the computing device 4002 may implement the
computer-executable instructions 4010 and output a result to (and/or
receive data from) the computing device 4004. Since the computing device
4002 may be wholly or partially contained within the computing device
4004, the device 4004 also may be said to execute some or all of the
computer-executable instructions 4010, in order to be caused to perform
or implement, for example, various ones of the techniques described
herein, or other techniques.

[0215]The device 4004 may include, for example, a portable computing
device, workstation, or desktop computing device. In another example
embodiment, the computing device 4002 is operable to communicate with the
device 4004 associated with the user 118 to receive information about the
input from the user 118 for performing data access and data processing
and presenting an output of the user-health test function at least partly
based on the user data.

[0216]Although a user 140 is shown/described herein as a single
illustrated figure, those skilled in the art will appreciate that a user
140 may be representative of a human user, a robotic user (e.g.,
computational entity), and/or substantially any combination thereof
(e.g., a user may be assisted by one or more robotic agents). In
addition, a user 140, as set forth herein, although shown as a single
entity may in fact be composed of two or more entities. Those skilled in
the art will appreciate that, in general, the same may be said of
"sender" and/or other entity-oriented terms as such terms are used
herein.

[0217]Those skilled in the art will appreciate that the foregoing specific
exemplary processes and/or devices and/or technologies are representative
of more general processes and/or devices and/or technologies taught
elsewhere herein, such as in the claims filed herewith and/or elsewhere
in the present application.

[0218]Those having skill in the art will recognize that the state of the
art has progressed to the point where there is little distinction left
between hardware, software, and/or firmware implementations of aspects of
systems; the use of hardware, software, and/or firmware is generally (but
not always, in that in certain contexts the choice between hardware and
software can become significant) a design choice representing cost vs.
efficiency tradeoffs. Those having skill in the art will appreciate that
there are various vehicles by which processes and/or systems and/or other
technologies described herein can be effected (e.g., hardware, software,
and/or firmware), and that the preferred vehicle will vary with the
context in which the processes and/or systems and/or other technologies
are deployed. For example, if an implementer determines that speed and
accuracy are paramount, the implementer may opt for a mainly hardware
and/or firmware vehicle; alternatively, if flexibility is paramount, the
implementer may opt for a mainly software implementation; or, yet again
alternatively, the implementer may opt for some combination of hardware,
software, and/or firmware. Hence, there are several possible vehicles by
which the processes and/or devices and/or other technologies described
herein may be effected, none of which is inherently superior to the other
in that any vehicle to be utilized is a choice dependent upon the context
in which the vehicle will be deployed and the specific concerns (e.g.,
speed, flexibility, or predictability) of the implementer, any of which
may vary. Those skilled in the art will recognize that optical aspects of
implementations will typically employ optically-oriented hardware,
software, and or firmware.

[0219]In some implementations described herein, logic and similar
implementations may include software or other control structures suitable
to operation. Electronic circuitry, for example, may manifest one or more
paths of electrical current constructed and arranged to implement various
logic functions as described herein. In some implementations, one or more
media are configured to bear a device-detectable implementation if such
media hold or transmit a special-purpose device instruction set operable
to perform as described herein. In some variants, for example, this may
manifest as an update or other modification of existing software or
firmware, or of gate arrays or other programmable hardware, such as by
performing a reception of or a transmission of one or more instructions
in relation to one or more operations described herein. Alternatively or
additionally, in some variants, an implementation may include
special-purpose hardware, software, firmware components, and/or
general-purpose components executing or otherwise invoking
special-purpose components. Specifications or other implementations may
be transmitted by one or more instances of tangible transmission media as
described herein, optionally by packet transmission or otherwise by
passing through distributed media at various times.

[0220]Alternatively or additionally, implementations may include executing
a special-purpose instruction sequence or otherwise invoking circuitry
for enabling, triggering, coordinating, requesting, or otherwise causing
one or more occurrences of any functional operations described above. In
some variants, operational or other logical descriptions herein may be
expressed directly as source code and compiled or otherwise invoked as an
executable instruction sequence. In some contexts, for example, C++ or
other code sequences can be compiled directly or otherwise implemented in
high-level descriptor languages (e.g., a logic-synthesizable language, a
hardware description language, a hardware design simulation, and/or other
such similar mode(s) of expression). Alternatively or additionally, some
or all of the logical expression may be manifested as a Verilog-type
hardware description or other circuitry model before physical
implementation in hardware, especially for basic operations or
timing-critical applications. Those skilled in the art will recognize how
to obtain, configure, and optimize suitable transmission or computational
elements, material supplies, actuators, or other common structures in
light of these teachings.

[0221]The foregoing detailed description has set forth various embodiments
of the devices and/or processes via the use of block diagrams,
flowcharts, and/or examples. Insofar as such block diagrams, flowcharts,
and/or examples contain one or more functions and/or operations, it will
be understood by those within the art that each function and/or operation
within such block diagrams, flowcharts, or examples can be implemented,
individually and/or collectively, by a wide range of hardware, software,
firmware, or virtually any combination thereof. In one embodiment,
several portions of the subject matter described herein may be
implemented via Application Specific Integrated Circuits (ASICs), Field
Programmable Gate Arrays (FPGAs), digital signal processors (DSPs), or
other integrated formats. However, those skilled in the art will
recognize that some aspects of the embodiments disclosed herein, in whole
or in part, can be equivalently implemented in integrated circuits, as
one or more computer programs running on one or more computers (e.g., as
one or more programs running on one or more computer systems), as one or
more programs running on one or more processors (e.g., as one or more
programs running on one or more microprocessors), as firmware, or as
virtually any combination thereof, and that designing the circuitry
and/or writing the code for the software and or firmware would be well
within the skill of one of skill in the art in light of this disclosure.
In addition, those skilled in the art will appreciate that the mechanisms
of the subject matter described herein are capable of being distributed
as a program product in a variety of forms, and that an illustrative
embodiment of the subject matter described herein applies regardless of
the particular type of signal bearing medium used to actually carry out
the distribution. Examples of a signal bearing medium include, but are
not limited to, the following: a recordable type medium such as a floppy
disk, a hard disk drive, a Compact Disc (CD), a Digital Video Disk (DVD),
a digital tape, a computer memory, etc.; and a transmission type medium
such as a digital and/or an analog communication medium (e.g., a fiber
optic cable, a waveguide, a wired communications link, a wireless
communication link (e.g., transmitter, receiver, transmission logic,
reception logic, etc.), etc.).

[0222]In a general sense, those skilled in the art will recognize that the
various embodiments described herein can be implemented, individually
and/or collectively, by various types of electro-mechanical systems
having a wide range of electrical components such as hardware, software,
firmware, and/or virtually any combination thereof; and a wide range of
components that may impart mechanical force or motion such as rigid
bodies, spring or torsional bodies, hydraulics, electro-magnetically
actuated devices, and/or virtually any combination thereof. Consequently,
as used herein "electro-mechanical system" includes, but is not limited
to, electrical circuitry operably coupled with a transducer (e.g., an
actuator, a motor, a piezoelectric crystal, a Micro Electro Mechanical
System (MEMS), etc.), electrical circuitry having at least one discrete
electrical circuit, electrical circuitry having at least one integrated
circuit, electrical circuitry having at least one application specific
integrated circuit, electrical circuitry forming a general purpose
computing device configured by a computer program (e.g., a general
purpose computer configured by a computer program which at least
partially carries out processes and/or devices described herein, or a
microprocessor configured by a computer program which at least partially
carries out processes and/or devices described herein), electrical
circuitry forming a memory device (e.g., forms of memory (e.g., random
access, flash, read only, etc.)), electrical circuitry forming a
communications device (e.g., a modem, communications switch,
optical-electrical equipment, etc.), and/or any non-electrical analog
thereto, such as optical or other analogs. Those skilled in the art will
also appreciate that examples of electro-mechanical systems include but
are not limited to a variety of consumer electronics systems, medical
devices, as well as other systems such as motorized transport systems,
factory automation systems, security systems, and/or
communication/computing systems. Those skilled in the art will recognize
that electro-mechanical as used herein is not necessarily limited to a
system that has both electrical and mechanical actuation except as
context may dictate otherwise.

[0223]In a general sense, those skilled in the art will recognize that the
various aspects described herein which can be implemented, individually
and/or collectively, by a wide range of hardware, software, firmware,
and/or any combination thereof can be viewed as being composed of various
types of "electrical circuitry." Consequently, as used herein "electrical
circuitry" includes, but is not limited to, electrical circuitry having
at least one discrete electrical circuit, electrical circuitry having at
least one integrated circuit, electrical circuitry having at least one
application specific integrated circuit, electrical circuitry forming a
general purpose computing device configured by a computer program (e.g.,
a general purpose computer configured by a computer program which at
least partially carries out processes and/or devices described herein, or
a microprocessor configured by a computer program which at least
partially carries out processes and/or devices described herein),
electrical circuitry forming a memory device (e.g., forms of memory
(e.g., random access, flash, read only, etc.)), and/or electrical
circuitry forming a communications device (e.g., a modem, communications
switch, optical-electrical equipment, etc.). Those having skill in the
art will recognize that the subject matter described herein may be
implemented in an analog or digital fashion or some combination thereof.

[0224]Those skilled in the art will recognize that at least a portion of
the devices and/or processes described herein can be integrated into a
data processing system. Those having skill in the art will recognize that
a data processing system generally includes one or more of a system unit
housing, a video display device, memory such as volatile or non-volatile
memory, processors such as microprocessors or digital signal processors,
computational entities such as operating systems, drivers, graphical user
interfaces, and applications programs, one or more interaction devices
(e.g., a touch pad, a touch screen, an antenna, etc.), and/or control
systems including feedback loops and control motors (e.g., feedback for
sensing position and/or velocity; control motors for moving and/or
adjusting components and/or quantities). A data processing system may be
implemented utilizing suitable commercially available components, such as
those typically found in data computing/communication and/or network
computing/communication systems.

[0225]Those skilled in the art will recognize that it is common within the
art to implement devices and/or processes and/or systems, and thereafter
use engineering and/or other practices to integrate such implemented
devices and/or processes and/or systems into more comprehensive devices
and/or processes and/or systems. That is, at least a portion of the
devices and/or processes and/or systems described herein can be
integrated into other devices and/or processes and/or systems via a
reasonable amount of experimentation. Those having skill in the art will
recognize that examples of such other devices and/or processes and/or
systems might include--as appropriate to context and application--all or
part of devices and/or processes and/or systems of (a) an air conveyance
(e.g., an airplane, rocket, helicopter, etc.), (b) a ground conveyance
(e.g., a car, truck, locomotive, tank, armored personnel carrier, etc.),
(c) a building (e.g., a home, warehouse, office, etc.), (d) an appliance
(e.g., a refrigerator, a washing machine, a dryer, etc.), (e) a
communications system (e.g., a networked system, a telephone system, a
Voice over IP system, etc.), (f) a business entity (e.g., an Internet
Service Provider (ISP) entity such as Comcast Cable, Qwest, Southwestern
Bell, etc.), or (g) a wired/wireless services entity (e.g., Sprint,
Cingular, Nextel, etc.), etc.

[0226]In certain cases, use of a system or method may occur in a territory
even if components are located outside the territory. For example, in a
distributed computing context, use of a distributed computing system may
occur in a territory even though parts of the system may be located
outside of the territory (e.g., relay, server, processor, signal-bearing
medium, transmitting computer, receiving computer, etc. located outside
the territory).

[0227]A sale of a system or method may likewise occur in a territory even
if components of the system or method are located and/or used outside the
territory.

[0228]Further, implementation of at least part of a system for performing
a method in one territory does not preclude use of the system in another
territory.

[0229]All of the above U.S. patents, U.S. patent application publications,
U.S. patent applications, foreign patents, foreign patent applications
and non-patent publications referred to in this specification and/or
listed in any Application Data Sheet, are incorporated herein by
reference, to the extent not inconsistent herewith.

[0230]One skilled in the art will recognize that the herein described
components (e.g., operations), devices, objects, and the discussion
accompanying them are used as examples for the sake of conceptual clarity
and that various configuration modifications are contemplated.
Consequently, as used herein, the specific exemplars set forth and the
accompanying discussion are intended to be representative of their more
general classes. In general, use of any specific exemplar is intended to
be representative of its class, and the non-inclusion of specific
components (e.g., operations), devices, and objects should not be taken
limiting.

[0231]With respect to the use of substantially any plural and/or singular
terms herein, those having skill in the art can translate from the plural
to the singular and/or from the singular to the plural as is appropriate
to the context and/or application. The various singular/plural
permutations are not expressly set forth herein for sake of clarity.

[0232]The herein described subject matter sometimes illustrates different
components contained within, or connected with, different other
components. It is to be understood that such depicted architectures are
merely exemplary, and that in fact many other architectures may be
implemented which achieve the same functionality. In a conceptual sense,
any arrangement of components to achieve the same functionality is
effectively "associated" such that the desired functionality is achieved.
Hence, any two components herein combined to achieve a particular
functionality can be seen as "associated with" each other such that the
desired functionality is achieved, irrespective of architectures or
intermedial components. Likewise, any two components so associated can
also be viewed as being "operably connected", or "operably coupled," to
each other to achieve the desired functionality, and any two components
capable of being so associated can also be viewed as being "operably
couplable," to each other to achieve the desired functionality. Specific
examples of operably couplable include but are not limited to physically
mateable and/or physically interacting components, and/or wirelessly
interactable, and/or wirelessly interacting components, and/or logically
interacting, and/or logically interactable components.

[0234]While particular aspects of the present subject matter described
herein have been shown and described, it will be apparent to those
skilled in the art that, based upon the teachings herein, changes and
modifications may be made without departing from the subject matter
described herein and its broader aspects and, therefore, the appended
claims are to encompass within their scope all such changes and
modifications as are within the true spirit and scope of the subject
matter described herein. It will be understood by those within the art
that, in general, terms used herein, and especially in the appended
claims (e.g., bodies of the appended claims) are generally intended as
"open" terms (e.g., the term "including" should be interpreted as
"including but not limited to," the term "having" should be interpreted
as "having at least," the term "includes" should be interpreted as
"includes but is not limited to," etc.). It will be further understood by
those within the art that if a specific number of an introduced claim
recitation is intended, such an intent will be explicitly recited in the
claim, and in the absence of such recitation no such intent is present.
For example, as an aid to understanding, the following appended claims
may contain usage of the introductory phrases "at least one" and "one or
more" to introduce claim recitations. However, the use of such phrases
should not be construed to imply that the introduction of a claim
recitation by the indefinite articles "a" or "an" limits any particular
claim containing such introduced claim recitation to claims containing
only one such recitation, even when the same claim includes the
introductory phrases "one or more" or "at least one" and indefinite
articles such as "a" or "an" (e.g., "a" and/or "an" should typically be
interpreted to mean "at least one" or "one or more"); the same holds true
for the use of definite articles used to introduce claim recitations. In
addition, even if a specific number of an introduced claim recitation is
explicitly recited, those skilled in the art will recognize that such
recitation should typically be interpreted to mean at least the recited
number (e.g., the bare recitation of "two recitations," without other
modifiers, typically means at least two recitations, or two or more
recitations). Furthermore, in those instances where a convention
analogous to "at least one of A, B, and C, etc." is used, in general such
a construction is intended in the sense one having skill in the art would
understand the convention (e.g., "a system having at least one of A, B,
and C" would include but not be limited to systems that have A alone, B
alone, C alone, A and B together, A and C together, B and C together,
and/or A, B, and C together, etc.). In those instances where a convention
analogous to "at least one of A, B, or C, etc." is used, in general such
a construction is intended in the sense one having skill in the art would
understand the convention (e.g., "a system having at least one of A, B,
or C" would include but not be limited to systems that have A alone, B
alone, C alone, A and B together, A and C together, B and C together,
and/or A, B, and C together, etc.). It will be further understood by
those within the art that typically a disjunctive word and/or phrase
presenting two or more alternative terms, whether in the description,
claims, or drawings, should be understood to contemplate the
possibilities of including one of the terms, either of the terms, or both
terms unless context dictates otherwise. For example, the phrase "A or B"
will be typically understood to include the possibilities of "A" or "B"
or "A and B."

[0235]With respect to the appended claims, those skilled in the art will
appreciate that recited operations therein may generally be performed in
any order. Also, although various operational flows are presented in a
sequence(s), it should be understood that the various operations may be
performed in other orders than those which are illustrated, or may be
performed concurrently. Examples of such alternate orderings may include
overlapping, interleaved, interrupted, reordered, incremental,
preparatory, supplemental, simultaneous, reverse, or other variant
orderings, unless context dictates otherwise. Furthermore, terms like
"responsive to," "related to," or other past-tense adjectives are
generally not intended to exclude such variants, unless context dictates
otherwise.

[0236]While various aspects and embodiments have been disclosed herein,
other aspects and embodiments will be apparent to those skilled in the
art. The various aspects and embodiments disclosed herein are for
purposes of illustration and are not intended to be limiting, with the
true scope and spirit being indicated by the following claims.